The level crossings in the United States experience a significant number of accidents every year. The accidents can be reduced with the application of various countermeasures (e.g., traffic signal preemption, flashing lights, barrier cubs, gates). However, the application of countermeasures for all the level crossings in the United States is not feasible due to monetary limitations. Moreover, each countermeasure has a unique level of effectiveness and installation cost (e.g., the most effective countermeasures are typically more expensive than the least effective ones). Hence, selection of potent and cost-effective countermeasures at the riskiest level crossings is imperative to improve safety. While improving safety at level crossings with the application of countermeasures, there is a significant risk of waning highway vehicle flows, increasing delays, and negatively affecting the continuity of passenger and freight flows. In such a scenario, multi-objective resource allocation models could be instrumental, since such models can analyze the tradeoffs between conflicting objectives (e.g., minimizing the number of accidents vs. minimizing the total delay). Hence, this chapter presents a framework for multi-objective resource allocation to minimize the number of accidents and to minimize the total delay at level crossings. Furthermore, various methods for quantifying the number of accidents as well as delays due to the application of countermeasures at level crossings are reviewed. Solution methods for multi-objective resource allocation models, including exact and approximate optimization approaches, are also discussed. Finally, future research avenues for multi-objective resource allocation among level crossings are outlined.