The authors address strategic planning problems for emergency medical systems (EMS). In particular, the three following critical decisions are considered: i) how many ambulances to deploy in a given territory at any given point in time, to meet the forecasted demand, yielding an appropriate response time; ii) when ambulances should be used for serving nonurgent requests and when they should better be kept idle for possible incoming urgent requests; iii) how to define an optimal mix of contracts for renting ambulances from private associations to meet the forecasted demand at minimum cost. In particular, analytical models for decision support, based on queuing theory, discrete-event simulation, and integer linear programming were presented. Computational experiments have been done on real data from the city of Milan, Italy.