This work studies the ambulance location problem for the Red Cross in Tijuana, Baja California , Mexico. The solution to the ambulance location problem is to optimally locate all available ambulances within the city such that coverage of the city population is maximized and a quick response to any emergency is ensured. The problem is posed using three different coverage models; namely the Location Set Covering Model (LSCM), the Maximal Covering Location Problem (MCLP) and the Double Standard Model (DSM), also we proposed robust versions of each model, where the goal was to find a single solution that might provide optima coverage in several different scenarios. Using real-world data collected from over 44,000 emergency calls received by the Red Cross of Tijuana, several scenarios were generated that provide different perspectives of the demand throughout the city, considering such factors as the time of day, work and off-days, geographical organization and call priority. These scenarios are solved using Integer Linear Programming and the solutions are compared with the current locations used by the Red Cross. Results show that demand coverage and response times can be substantially improved without additional resources.