A highway-railroad grade crossing (HRGX) is a spatial location where highway and rail users share the same right-of-way. Despite the number of HRGXs managed by the Taiwan Railways Administration (TRA) is relatively few, a significant number of traffic collisions and severe consequences at the HRGXs in Taiwan has signaled an urgent need for appropriate models to identify the key factors that are associated with the casualty risk levels of an HRGX. This study uses counted data statistical models where Poisson, negative binominal and zero-inflated Poisson regression models are evaluated to analyze crash frequency and risk levels in terms of number of fatalities and injuries in a given time period. Besides, crash severity in terms of number of equivalent injuries per traffic collision is modeled by the ordered logistic regression approach. In the empirical study, using the recent crash and HRGX inventory data provided by the TRA, this study aims to analyze the causal relationships between crash frequency and/or severity and a set of influence factors. The empirical study results indicate that traffic exposure related variables such as daily trains and/or highway average annual daily traffic are the key factors. Besides, grade crossing width and highway type also play different roles on the occurrence and/or consequence of a traffic collision(s) at HRGXs. Finally, elasticity and odds ratio analysis based on the calibrated models are also conducted. The ultimate goal of this research is to provide the HGRX administrative office with a reference before implementing related countermeasures for safety improvement.