Performance models provide significant insight into the performance relationships between an application and the system, either parallel or distributed, used for execution. The development of models often requires significant time, sometimes in the range of months, to develop; this is especially the case for detailed models. This paper presents our approach to reducing the time required for model development. We present the concept of an automated model builder within the Prophesy infrastructure, which also includes automated instrumentation and extensive databases for archiving the performance data. In particular, we focus on the automation of the development of analytical performance models. The concepts include the automation of some well-established techniques, such as curve fitting, and a new technique that develops models as a composition of other models of core components or kernels in the application.