Run-off-road crashes in the United States have become a major cause of serious injuries and fatalities. A significant portion of run-off-road crashes are single vehicle crashes that occur due to collisions with fixed objects and overturning. These crashes typically tend to be more severe than other types of crashes. Single vehicle run-off-road crashes that occurred between 2004 and 2008 were extracted from Kansas Accident Reporting System (KARS) database to identify the important factors that affected their severity. Different driver, vehicle, road, crash, and environment related factors that influence crash severity are identified by using binary logit models. Three models were developed to take different levels of crash severity as the response variables. The first model taking fatal or incapacitating crashes as the response variable seems to better fit the data than the other two developed models. The variables that were found to increase the probability of run-off-road crash severity are driver related factors such as driver ejection, being an older driver, alcohol involvement, license state, driver being at fault, medical condition of the driver; road related factors such as speed, asphalt road surface, dry road condition; time related factors such as crashes occurring between 6 pm and midnight; environment related factors such as daylight; vehicle related factors such as being an SUV, motorcycles, vehicle getting destroyed or disabled, vehicle maneuver being straight or passing; and fixed object types such as trees and ditches.
 Fatality Accident Report System, “National Highway Traffic Safety Administration, US Department of Transportation, 2011.
 U.S. Department of Transportation (USDOT), “Federal Highway Administration. Strategic Highway Safety Plan: A Champion’s Guide to Saving Lives,” Washington DC, 2010. http://safety.fhwa.dot.gov/hsip/
 National Highway Traffic Safety Administration (NHTSA), “Traffic Safety Facts 2003: A Compilation of Motor Vehicle Crash Data from the Fatality Analysis Reporting System and the General Estimates System,” National Highway Traffic Safety Administration, US Department of Transportation, Washington DC.
 R. K. Young and J. Liesman, “Estimating of the Relationship between Measured Wind Speed and Overturning Truck Crashes Using a Binary Logit Model,” Accident Analysis and Prevention, Vol. 39, No. 3, 2007, pp. 574-580.
 H. Zhu, K. K. Dixon, S. Washington and D. M. Jared, “Single-Vehicle Fatal Crash Prediction for Two-Lane Rural Highways in the Southeastern United States,” Preprint CD-ROM of the 89th Annual Meeting of TRB, National Research Council, Washington DC, 2010.
 J. Lee and F. Mannering, “Analysis of Roadside Accident Frequency and Severity and Roadside Safety Management,” Prepared by Washington State Transportation Center for Washington State Transportation Commission, Department of Transportation, 1999.
 L. K. Spainhour and A. Mishra, “Analysis of Fatal Run-off-the-Road Crashes Involving Overcorrection,” Journal of Transportation Research Record, Vol. 2069, National Research Council, Washington DC, 2008.
 D. Noyce, J. Wahid, A. R. Bill and K. Santiago, “The Operational and Safety Impacts of ROR Crashes in Wisconsin: Object Hits and Ramp Terminals,” Prepared by Traffic Operations and Safety Laboratory, Department of Civil Engineering, University of Wisconsin-Madison, Prepared for Wisconsin Department of Transportation, 2008.
 L. I. Ratnayake, “Developing and Testing of Methodologies to Estimate Benefits Associated with Seat Belt Usage in Kansas,” A Dissertation Submitted in Partial Fulfillment for the Degree of Doctor of Philosophy, Kansas State University, Manhattan, 2007.