City crime ranking
100 Cities with Lowest Property Crime
Ranked by lowest property crime rate per 100,000 population. Includes cities with 25,000+ residents.
- 100
- Cities ranked
- 0/100K
- Lowest rate
- 1,632.1/100K
- Cohort median (1,709 cities)
The ranking in one line
Savannah, GA has the lowest property crime rate in America at 0 per 100,000. Every one of the 100 lowest-property-crime cities reports below 538.4 per 100,000, and they span 26 states.
- 100
- cities ranked
- 538.4/100K
- highest rate that still makes the top 100
- 1,632.1/100K
- cohort median across all 1,709 eligible cities (25,000+ population)
- 26
- states represented in the top 100
Read before you rank
This ranking measures reported property crime, not overall safety. FBI UCR participation is voluntary and reporting completeness varies by city and year, so a low rate can reflect genuinely less crime or a less complete report. Property crime also excludes violent offenses entirely, check a city's violent-crime rate separately before drawing conclusions. For scale: the median rate across all 1,709 eligible cities is 1,632.1 per 100,000. The #1 city's rate is only 0% of that median, an unusually low reading worth reading alongside the raw incident count.
How low is low? The top-100 cutoff vs. every US city
Property crime per 100,000 residents, latest FBI UCR data
538 Safer than 72% among 8,986 US cities
Each bar is a band of values; taller bars hold more US cities. The dashed line + filled bar mark this entry. Hover or tap any bar for its full count, share, and where it sits relative to this entry.
Source FBI Uniform Crime Reporting (UCR) Program · 2024
| # | City | State | Population | Property Crime Rate |
|---|---|---|---|---|
| 1 | Savannah | Georgia | 241,780 | 0/100K |
| 2 | Worcester | Massachusetts | 212,425 | 0/100K |
| 3 | Barnegat Township | New Jersey | 26,713 | 78.6/100K |
| 4 | Columbus | Indiana | 51,867 | 82.9/100K |
| 5 | Long Beach | New York | 34,527 | 104.3/100K |
| 6 | Raritan Township | New Jersey | 25,018 | 119.9/100K |
| 7 | Plum | Pennsylvania | 26,145 | 153/100K |
| 8 | Marshfield | Massachusetts | 26,238 | 167.7/100K |
| 9 | Lone Peak | Utah | 30,812 | 168.8/100K |
| 10 | Bernards Township | New Jersey | 28,921 | 176.3/100K |
| 11 | Bridgewater | Massachusetts | 29,465 | 200.2/100K |
| 12 | Bergenfield | New Jersey | 28,879 | 232/100K |
| 13 | Hampden Township | Pennsylvania | 35,576 | 238.9/100K |
| 14 | Centerton | Arkansas | 26,233 | 240.2/100K |
| 15 | Monroe Township, Middlesex County | New Jersey | 49,652 | 261.8/100K |
| 16 | Lyon Township | Michigan | 26,094 | 268.3/100K |
| 17 | Genoa Township | Ohio | 28,085 | 270.6/100K |
| 18 | Zionsville | Indiana | 33,121 | 277.8/100K |
| 19 | Franklin | Massachusetts | 33,716 | 287.7/100K |
| 20 | Avon Lake | Ohio | 26,167 | 290.4/100K |
| 21 | Randolph Township | New Jersey | 27,159 | 290.9/100K |
| 22 | Northampton Township | Pennsylvania | 39,879 | 293.4/100K |
| 23 | Northern Regional | Pennsylvania | 38,548 | 303.5/100K |
| 24 | Amherst | Massachusetts | 46,304 | 306.7/100K |
| 25 | Independence | Kentucky | 29,747 | 316/100K |
| 26 | Independence Township | Michigan | 37,059 | 323.8/100K |
| 27 | Lexington | Massachusetts | 34,350 | 334.8/100K |
| 28 | Melissa | Texas | 27,831 | 341.3/100K |
| 29 | Merrimack | New Hampshire | 29,650 | 344/100K |
| 30 | Westtown-East Goshen Regional | Pennsylvania | 29,610 | 351.2/100K |
| 31 | Newtown | Connecticut | 27,890 | 351.4/100K |
| 32 | Fulshear | Texas | 26,048 | 364.7/100K |
| 33 | Brandon | Mississippi | 25,905 | 374.4/100K |
| 34 | Hamilton Township, Warren County | Ohio | 28,313 | 377.9/100K |
| 35 | Brunswick | Ohio | 34,952 | 383.4/100K |
| 36 | Cheshire | Connecticut | 29,399 | 384.4/100K |
| 37 | Yorkville | Illinois | 25,788 | 387.8/100K |
| 38 | Madison | Mississippi | 28,064 | 388.4/100K |
| 39 | Northern Lancaster County Regional | Pennsylvania | 41,609 | 389.3/100K |
| 40 | Hillsborough Township | New Jersey | 45,555 | 390.7/100K |
| 41 | Bartlett | Illinois | 39,656 | 390.9/100K |
| 42 | Northern York County Regional | Pennsylvania | 90,901 | 399.3/100K |
| 43 | Orion Township | Michigan | 35,833 | 404.7/100K |
| 44 | East Fishkill Town | New York | 29,607 | 405.3/100K |
| 45 | Wakefield | Massachusetts | 28,594 | 409.2/100K |
| 46 | North Augusta | South Carolina | 26,377 | 409.4/100K |
| 47 | Billerica | Massachusetts | 42,332 | 411/100K |
| 48 | Beverly | Massachusetts | 43,024 | 411.4/100K |
| 49 | Hanover Park | Illinois | 35,779 | 416.4/100K |
| 50 | Little Elm | Texas | 62,837 | 423.3/100K |
| 51 | Mahwah Township | New Jersey | 25,873 | 425.2/100K |
| 52 | Jackson Township | New Jersey | 62,326 | 428.4/100K |
| 53 | Huntley | Illinois | 28,439 | 429/100K |
| 54 | Melrose | Massachusetts | 29,784 | 429.8/100K |
| 55 | Arlington | Massachusetts | 46,956 | 434.4/100K |
| 56 | White Lake Township | Michigan | 31,222 | 435.6/100K |
| 57 | Lake in the Hills | Illinois | 28,573 | 437.5/100K |
| 58 | Oak Forest | Illinois | 25,823 | 437.6/100K |
| 59 | Belvidere | Illinois | 25,302 | 438.7/100K |
| 60 | Londonderry | New Hampshire | 26,974 | 444.9/100K |
| 61 | Perrysburg | Ohio | 25,302 | 446.6/100K |
| 62 | Middletown Township | Pennsylvania | 45,516 | 448.2/100K |
| 63 | Milton | Georgia | 41,603 | 449.5/100K |
| 64 | Wallingford | Connecticut | 43,561 | 449.9/100K |
| 65 | Manchester Township | New Jersey | 47,488 | 450.6/100K |
| 66 | Glen Cove | New York | 27,767 | 468.2/100K |
| 67 | Caledonia | Wisconsin | 25,323 | 469.9/100K |
| 68 | Rockville Centre Village | New York | 25,472 | 471.1/100K |
| 69 | Harrison Town | New York | 31,718 | 476.1/100K |
| 70 | O'Fallon | Missouri | 94,911 | 479.4/100K |
| 71 | Fate | Texas | 27,141 | 482.7/100K |
| 72 | Ballwin | Missouri | 30,171 | 483.9/100K |
| 73 | Wellesley | Massachusetts | 31,973 | 484.8/100K |
| 74 | Bella Vista | Arkansas | 33,122 | 489.1/100K |
| 75 | Hazleton | Pennsylvania | 30,079 | 492/100K |
| 76 | Radnor Township | Pennsylvania | 33,908 | 495.5/100K |
| 77 | Marion | Iowa | 42,420 | 497.4/100K |
| 78 | Spring Hill | Tennessee | 59,921 | 499/100K |
| 79 | Rosemount | Minnesota | 28,220 | 499.6/100K |
| 80 | Syracuse | Utah | 38,714 | 501.1/100K |
| 81 | Maryville | Tennessee | 32,583 | 506.4/100K |
| 82 | York County Regional | Pennsylvania | 71,232 | 511/100K |
| 83 | Mount Olive Township | New Jersey | 30,034 | 512.8/100K |
| 84 | Ramsey | Minnesota | 28,813 | 517.1/100K |
| 85 | Windsor | Colorado | 43,050 | 520.3/100K |
| 86 | Rexburg | Idaho | 40,164 | 522.9/100K |
| 87 | Rancho Santa Margarita | California | 45,633 | 523.7/100K |
| 88 | West Bloomfield Township | Michigan | 64,892 | 525.5/100K |
| 89 | Mason | Ohio | 35,923 | 528.9/100K |
| 90 | Menomonee Falls | Wisconsin | 40,076 | 529/100K |
| 91 | Upper Macungie Township | Pennsylvania | 29,196 | 530.9/100K |
| 92 | Crown Point | Indiana | 35,185 | 531.5/100K |
| 93 | Kaysville | Utah | 32,915 | 531.7/100K |
| 94 | Rochester Hills | Michigan | 75,960 | 531.9/100K |
| 95 | Reading | Massachusetts | 25,871 | 533.4/100K |
| 96 | Cumberland | Rhode Island | 37,213 | 534.8/100K |
| 97 | Calexico | California | 38,106 | 535.3/100K |
| 98 | Johns Creek | Georgia | 81,056 | 536.7/100K |
| 99 | Colleyville | Texas | 25,630 | 538.4/100K |
| 100 | Noblesville | Indiana | 75,216 | 538.4/100K |
Property Crime Rate Distribution, 100 Lowest-Property-Crime Cities
Property crime rates per 100,000 residents. Hover a bar for the exact count.
- 0–500
0–500
79 cities
- 500–1,000 21
500–1,000
21 cities
Source: FBI Uniform Crime Reporting (UCR) Program FBI Uniform Crime Reporting (UCR) Program Cities with population under 25,000 are excluded
How violent and property crime are reported in U.S. cities
City-level crime rates published on PlainCrime come from the FBI Uniform Crime Reporting (UCR) Program, which has compiled offense counts from local law enforcement agencies since 1930. Each year, thousands of police departments submit standardized counts of Part I offenses, murder and non-negligent manslaughter, rape, robbery, aggravated assault, burglary, larceny-theft, motor vehicle theft, and arson, to a central FBI database. The UCR program supplies the raw counts; population denominators come from the U.S. Census Bureau, and per-capita rates are calculated by dividing the offense count by population and multiplying by 100,000.
Violent crime, the focus of this ranking, comprises murder, rape, robbery, and aggravated assault. These four categories cover incidents involving force, threat of force, or completed physical harm against a person. Robbery requires an interaction between victim and offender even when no weapon is used. Aggravated assault, the most common violent crime nationally, captures attacks intended to cause serious bodily injury or involving a weapon. Murder counts include both completed killings and non-negligent manslaughter, but exclude negligent manslaughter, justifiable homicide, and suicide.
Property crime, burglary, larceny-theft, motor vehicle theft, and arson, appears far more frequently than violent crime in nearly every U.S. jurisdiction. The national property-crime rate typically runs five to seven times higher than the violent-crime rate. Burglary requires unlawful entry into a structure with intent to commit a theft or felony; larceny-theft covers simple taking of property without force; motor vehicle theft is specifically the theft of a vehicle; and arson is the willful burning of a structure or property.
Why per-capita rates matter more than raw counts
Comparing a city of 8 million residents to a city of 50,000 residents using raw offense counts produces misleading results: the larger city will always show more crime because there are simply more people to victimize. Per-capita rates (crimes per 100,000 residents) correct for population so cities of different sizes can be compared on the same scale. PlainCrime restricts its city rankings to jurisdictions with at least 25,000 residents to avoid extreme rate volatility, in a city of 5,000 people, a single robbery moves the per-capita robbery rate by 20 points, which is statistically meaningless.
Even with the 25,000-resident floor, per-capita rates contain meaningful noise. A city that hosts a major tourism destination, university, or commuter hub will record offenses against non-residents, while its population denominator counts only permanent residents. This inflates the rate. Conversely, a city where many residents commute elsewhere may record fewer victimizations than the resident count would predict, deflating the rate. We surface these caveats on each city's detail page so users can interpret figures in context.
Limitations of FBI UCR data
UCR participation is voluntary. While most large cities submit consistently, gaps appear, some cities report only certain categories, and some agencies fail to report in given years. The 2021 transition from the legacy Summary Reporting System (SRS) to the National Incident-Based Reporting System (NIBRS) reduced reporting coverage temporarily as agencies migrated systems. We flag known reporting gaps on each city page and use the most recent year of data available for each jurisdiction.
The UCR also captures only crimes reported to law enforcement. The National Crime Victimization Survey, run separately by the Bureau of Justice Statistics, consistently finds that property crimes are reported only 30–40% of the time and violent crimes 40–50% of the time. UCR rates should be read as reported crime, not total crime. They remain the best available comparable national dataset.
Using PlainCrime rankings responsibly
Crime rankings are most useful when they sit alongside other community-quality signals, school performance, housing affordability, employment, and access to healthcare. A safer-than-average violent-crime rate in a small commuter suburb does not by itself make a city a better place to live; it is one data point among many. Likewise, a higher-than-average rate in a dense urban center may reflect that residents and visitors interact with police more often, not that the city is necessarily unsafe for its residents. We provide cross-links from each city profile to neighboring jurisdictions, state averages, and national benchmarks so you can read each number in context rather than in isolation.
For news outlets, researchers, and concerned residents who cite our rankings, the most defensible approach is to quote the per-100,000 rate, the reporting year, and the source agency in the same sentence. Avoid framing crime statistics as predictive, UCR data describes what was reported in a past year, not what will happen tomorrow. Where possible, pair our rankings with longitudinal trend data on the relevant city's profile page to show whether the rate is moving up, holding steady, or falling year over year.
Every figure on PlainCrime is rendered directly from FBI Uniform Crime Reporting (UCR) source data, no number is typed in by an editor. This page draws directly on FBI Uniform Crime Reporting source data, no figure is typed in by an editor. See our editorial standards & corrections policy, the methodology behind these numbers, or report a data error.