Road traffic accidents are among the most significant humanitarian crises, causing substantial loss of life and considerable economic and social costs worldwide. According to the World Health Organization, road traffic accidents claim approximately 1.19 million lives annually. This study aimed to develop and simulate a system dynamics model to improve the performance of road traffic accident response and rescue operations of the Iranian Red Crescent Society in Yazd Province. The model was developed based on real-world data from rescue and relief operations during 2018–2022. Key variables were identified through a literature review and expert judgment and organized into four subsystems: human resources, casualty response, training and empowerment, and communication and coordination. Subsequently, a stock-and-flow model was developed and validated using behavior reproduction, extreme conditions, and sensitivity analysis tests. Three policy scenarios—an increase in the training budget, reduction of nuisance calls through deterrent measures implemented by legally authorized institutions, and a combined policy—were simulated over the period from April 2022 to March 2025. The results showed that the nuisance-call reduction scenario decreased response time from 11.1 to 9.7 minutes (12.6%) and increased the triage rate from 227 to 268 persons (18.1%). Increasing the training budget raised the triage rate to 233 persons (2.6%). Under the combined scenario, the triage rate increased to 272 persons, representing a 19.8% improvement over the baseline and a 1.5% improvement over the nuisance-call reduction scenario. Therefore, the simultaneous implementation of both policies produced the greatest improvement in overall response performance.