The current methodology for prioritizing level crossing (LC) warning system upgrades and elimination in the United States (U.S.) focuses on the likelihood of collisions between highway and rail vehicles as well as highway user fatalities. However, these metrics do not encompass all LC risks. In particular, they do not consider the risk of derailment that LCs pose to trains, crews, and cargo (especially dangerous goods). Little previous research has considered this aspect of LC risk, although its impact is potentially severe. LCs have caused a number of train accidents in the U.S., including several that resulted in dangerous goods releases leading to injuries and fatalities. In this paper, we present a multi-factor statistical model that predicts the likelihood of a train derailment as a result of various LC parameters. The model was developed based on extensive data from the U.S. Department of Transportation’s Federal Railroad Administration. It extends and formalizes previous work that identified factors leading to increased derailment likelihood for freight trains in LC collisions such as involvement of heavy highway vehicles (e.g. trucks/lorries) and higher train and motor vehicle speeds. The new model accounts for train and locomotive weight as additional factors to quantify derailment likelihood. The goal is development of a comprehensive understanding of the risk that level crossings pose to railroads and train operations.