Yearly Traffic Safety Analysis

12,021 CRASHES IN
OHIO, OH
2025

All metrics benchmarked against2024

In Montgomery County, total vehicle crashes increased by 4.4% from 11,519 in 2024 to 12,021 in 2025. Despite the rise in overall collisions, the number of fatalities decreased by 10.6%, from 66 to 59. The most notable shift was a 9.0% increase in hit-and-run crashes, which rose from 2,611 to 2,847 year-over-year.

12,021

▲ 4.4%was 11,519

Total Crash Events

▼ -10.6%was 66

Persons Killed

5,206

▲ 2.5%was 5,080

Persons Injured

2,847

▲ 9.0%was 2,611

Hit-and-Run Crashes

Note: "Persons Killed" (59) counts individual fatalities across all crash events. "Fatal" in the severity table below (55) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Traffic collisions in Montgomery County trended upward in 2025, with total crashes increasing by 4.4% compared to the prior year. While the number of injuries saw a modest 2.5% increase from 5,080 to 5,206, the number of fatalities declined from 66 to 59. This indicates a higher volume of crashes but a lower rate of fatal outcomes.

2,847

Hit-and-Run Crashes — 2025

▲ 9.0% vs prior (2,611)

Hit-and-run crashes increased in 2025 compared to the previous year. The total count of hit-and-run incidents rose by 9.0%, from 2,611 in 2024 to 2,847 in 2025. This upward trend is also reflected in the hit-and-run rate, which increased from 22.7% to 23.7% of all crashes.

Vulnerable Road User Casualties

Pedestrians Killed

Prior: 12↓-8.3%

Motorists Killed

Prior: 54↓-11.1%

152

Pedestrians Injured

Prior: 150↑1.3%

5,054

Motorists Injured

Prior: 4,930↑2.5%

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes remained largely consistent year-over-year, with Friday being the day with the most incidents in both 2024 (1,984 crashes) and 2025 (1,908 crashes). However, the peak time for collisions shifted slightly later in the afternoon, moving from the 3 p.m. hour in 2024 (942 crashes) to the 4 p.m. hour in 2025 (989 crashes).

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While total crashes rose, the severity of outcomes showed a mixed but generally less fatal profile in 2025. The number of fatal crashes decreased from 61 to 55, and the fatal crash rate per 100 collisions fell from 0.53 to 0.46. Conversely, crashes involving serious injuries increased in both count (from 282 to 311) and proportion (from 2.4% to 2.6% of all crashes).

Severity is per crash event (most severe injury). 55 fatal crash events resulted in 59 persons killed.

Outcome by Severity (Crash Events)

Fatal55fatal crashes0.5%

↓-9.8%prior 61

Serious Injury311serious injury crashes2.6%

↑10.3%prior 282

Minor Injury2,064minor injury crashes17.2%

↑6.2%prior 1,943

Possible Injury1,218possible injury crashes10.1%

↑0.7%prior 1,209

No Injury8,373no injury crashes69.7%

↑4.3%prior 8,024

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record

Road & Environmental Conditions

Environmental conditions reported at crash scenes showed a significant year-over-year change related to winter weather. While the majority of crashes in both periods occurred in clear weather and on dry roads, the number of crashes in snow conditions nearly doubled, increasing from 295 in 2024 to 557 in 2025. Similarly, crashes on snowy road surfaces rose from 210 to 562.

Weather

Clear7,512 (62.5%)

↑0.8%prior 7,455

Cloudy2,433 (20.2%)

↑10.6%prior 2,199

Rain1,244 (10.3%)

↓-11.3%prior 1,402

Snow557 (4.6%)

↑88.8%prior 295

Other/Unknown206 (1.7%)

↑79.1%prior 115

Fog; Smog; Smoke23 (0.2%)

↓-14.8%prior 27

Sleet; Hail18 (0.1%)

↑20.0%prior 15

Freezing Rain or Freezing Drizzle17 (0.1%)

↑112.5%prior 8

Blowing Sand; Soil; Dirt; Snow7 (0.1%)

Severe Crosswinds4 (0.0%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash

Lighting

Daylight7,929 (66.0%)

↑5.3%prior 7,532

Dark - Lighted Roadway2,410 (20.0%)

↓-2.9%prior 2,481

Dark - Roadway Not Lighted768 (6.4%)

↑4.2%prior 737

Dawn/Dusk650 (5.4%)

↑11.7%prior 582

Dark - Unknown Roadway Lighting155 (1.3%)

↑89.0%prior 82

Other/Unknown109 (0.9%)

↑3.8%prior 105

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field

Road Surface

Dry9,142 (76.1%)

↑2.8%prior 8,890

Wet2,061 (17.1%)

↓-8.3%prior 2,247

Snow562 (4.7%)

↑167.6%prior 210

Ice126 (1.0%)

↑55.6%prior 81

Other/Unknown97 (0.8%)

↑22.8%prior 79

Slush27 (0.2%)

↑440.0%prior 5

Sand; Mud; Dirt; Oil; Gravel4 (0.0%)

Water (Standing; Moving)2 (0.0%)

↓-60.0%prior 5

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field

Vehicles & Demographics

The primary vehicle makes involved in crashes remained consistent between the two periods, with Chevrolet, Ford, and Honda being the top three in both years. Chevrolet-involved crashes decreased slightly from 3,780 to 3,656, while Honda-involved crashes increased from 1,890 to 2,102. The age distribution of persons involved in crashes also remained stable, with the 26-34 age group accounting for the largest share in both 2024 (16.0%) and 2025 (16.3%).

Top Vehicle Makes (23,007 vehicles)

CHEVROLET3,656 (15.9%)

↓-3.3%prior 3,780

FORD2,703 (11.7%)

↑2.0%prior 2,649

HONDA2,102 (9.1%)

↑11.2%prior 1,890

TOYOTA1,681 (7.3%)

↑0.4%prior 1,675

NISSAN1,244 (5.4%)

↑2.7%prior 1,211

DODGE1,125 (4.9%)

↑10.3%prior 1,020

KIA890 (3.9%)

↑13.5%prior 784

HYUNDAI870 (3.8%)

↓-1.0%prior 879

JEEP838 (3.6%)

↑11.9%prior 749

GMC662 (2.9%)

↑7.1%prior 618

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records

2,508 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (26,769 persons with recorded sex)

Male14,523 (54.3%)

↑3.8%prior 13,989

Female12,246 (45.7%)

↑3.7%prior 11,807

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Person-level records linked to crash events

Data Sources & Methodology

Primary Data Source

All crash data in this report is sourced from Ohio Crash Data (ODOT TIMS), accessed programmatically via the Csv Open Data API (SODA). This dataset contains official police-reported motor vehicle traffic crash records maintained by the reporting jurisdiction's law enforcement agency. Records are published to the open data portal by the municipality and are subject to the portal's terms of use.

Data Retrieval

Access method: Csv Open Data API (SoQL queries)
Data format: Structured JSON via REST API
Record types queried: Crash events, person records, and vehicle unit records
Date filter applied: 2025-01-01 through 2025-12-31
Report generated: July 5, 2026

Data Coverage

Reporting period: 2025-01-01 through 2025-12-31 (365 days)
Geographic scope: ohio, OH
Total crash records analyzed: 12,021
Total persons involved: 28,832
Total vehicles involved: 23,007

Analytical Methodology

Severity classification: Uses the KABCO injury scale (K=Fatal, A=Incapacitating injury, B=Non-incapacitating injury, C=Possible injury, O=No injury/property damage only), the standard classification in U.S. Model Minimum Uniform Crash Criteria (MMUCC). Severity is assigned per crash event based on the most severe injury in that crash. A single fatal crash (K) may involve multiple fatalities; therefore the "Persons Killed" count in the headline KPIs may differ from the "Fatal" crash count in the severity breakdown.
Contributing factors: Reflect the officer-determined primary contributory cause recorded at the time of the crash report. These are preliminary determinations and may not reflect final investigation findings.
Hit-and-run classification: Based on the hit-and-run indicator field in the official crash report, as determined by the responding officer at the scene.
Temporal analysis: Day-of-week and hour-of-day distributions are computed from the crash date/time timestamp in each record.
Demographics: Age and sex distributions are drawn from person-level records linked to each crash event. A single crash may involve multiple persons.
Vehicle data: Make information is drawn from vehicle unit records linked to each crash event.
AI commentary: Narrative sections are generated by Google Gemini (large language model) based on the structured data. Commentary is descriptive, not predictive, and should not be interpreted as expert opinion.

Limitations & Disclaimers

Only crashes reported to and documented by law enforcement are included. Minor incidents, unreported crashes, and near-misses are not captured in this dataset.
Data reflects conditions at the time of the initial police report and may be subject to subsequent corrections, reclassifications, or supplements by the reporting agency.
Open data portal records may experience a publication lag - recently occurring crashes may not yet appear in the dataset at the time of report generation.
AI-generated commentary is produced by a large language model and is intended to highlight patterns in the data. It does not constitute legal, medical, or professional analysis.
Percentages are calculated from reported data and are subject to rounding.

Non-Affiliation Disclosure

This report is produced independently by ThatCarHitMe.com (Injuria.ai). It is not affiliated with, endorsed by, or produced in partnership with any law enforcement agency, municipal government, state department of transportation, or the National Highway Traffic Safety Administration (NHTSA). Data is sourced from publicly available government open data portals.

Data License

The underlying crash data is provided under the municipality's Open Data Terms of Use and is made available to the public for unrestricted use. This analysis and report is © 2026 Injuria.ai and may be cited with attribution using the suggested citation below.

Corrections & Feedback

If you believe any data in this report is inaccurate or have questions about our methodology, please contact: data@injuria.ai. We are committed to accuracy and will issue corrections promptly.

Suggested Citation

ThatCarHitMe.com (Injuria.ai). "ohio, OH Crash Intelligence Report: 2025." Published July 5, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Ohio Crash Data (ODOT TIMS), Csv Open Data. Available at: https://thatcarhitme.com/crash-data/ohio/statewide/2025-annual-report

About the Publisher

ThatCarHitMe.com is a crash data intelligence platform developed by Injuria.ai, a legal technology company specializing in traffic safety analytics. We aggregate and analyze publicly available government crash data to produce structured intelligence reports for communities, researchers, journalists, and legal professionals. Our reports combine programmatic data retrieval from official open data portals with AI-assisted narrative analysis.

Questions about this report's data or methodology: data@injuria.ai

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12,021 CRASHES INOHIO, OH2025