Highway rail grade crossing safety has improved considerably in the past two decades. Among the reasons is investment in more effective warning systems. Such upgrades are costly and resources are limited so decisions on which crossings should receive these investments should be made so that they will have the greatest impact on improving safety. A key tool for prioritizing grade crossings warning system upgrades are analysis tools that are used to develop quantitative metrics of the likelihood of incidents given the characteristics of a crossing. These tools have received a great deal of research attention and part of the success in reducing grade crossing incidents can be attributed to their use. Less research has been devoted to development of a comprehensive, quantitative approach to measure the consequences of grade crossing incidents. Consequences are the other element of risk analysis so development of more accurate metrics for this aspect of grade crossing incidents will improve our understanding of grade crossing risk. This paper describes a statistical approach using US DOT data and other information to quantitatively predict consequences in terms of several metrics and under a variety of circumstances.