This study identifies and quantifies the effects of different risk factors that increase accident severity at railroad-highway grade crossings. The research is based on utilizing binary logit to analyze all vehicle-train accidents that occurred at railroad-highway grade crossings in the United States from 2005 to 2015. The study investigates the temporal stability of the identified risk factors throughout the analysis period to identify the most significant risk factors that are temporally stable. Age and gender of the driver were found to be the most-significant temporally-stable risk factors identified. It was also found that darkness and adverse weather conditions may reduce accident severity, but they were not temporally stable throughout the analysis period. Accidents related to young drivers were found to be less severe. The findings of this research have the potential to help decision makers develop policies and countermeasures that reduce the severity of injuries at railroad-highway grade crossings by focusing on risk factors that consistently exhibit significant effects on the severity of accidents.