We show in this paper how to evaluate the performance of skeleton-based high level parallel programs. Since many applications follow some commonly used algorithmic skeletons, we identify such skeletons and model them with process algebra in order to get relevant information about the performance of the application, and be able to take some “good” scheduling decisions. This concept is illustrated through the case study of the Pipeline skeleton, and a tool which generates automatically a set of models and solves them is presented. Some numerical results are provided, proving the efficiency of this approach.