Introduction: Operational models of prehospital care consider system effectiveness and response time as key indicators, given their impact on survival probability and the severity of sequelae in medical emergencies. Aiming to reduce the current average response time of 46 min at Bogotá’s Emergency and Urgency Regulatory Center, far above the 10-min international benchmark for prehospital care, this study identifies key factors influencing response time and their effects on system effectiveness using a Random Forest model. Objective: This article aims to determine the key factors that most influence the response time of Bogotá’s prehospital care system, to explain the system’s behavior and propose future strategies for improved effectiveness. Methods: A Random Forest model was used to identify variables influencing response time. Spatial dependence was evaluated using the algorithm’s proximity matrix to build spatial weights. Geographic coordinates were included as explanatory variables, and the model estimated each variable’s contribution to improving node purity in the decision trees. Key Results: Data analysis from Bogotá shows a strong influence of incident location on response time. Additionally, the service provider and vehicle type used in transporting patients were also significant factors.