In this paper, we present a two-phase design space exploration (DSE) approach to address the problem of real-time application mapping on a flexible MPSoC platform. Our approach is composed of two independent phases - analytical estimation/pruning and system simulation - communicating via a well-defined interface. The strength of the resulting strategy is twofold. On one hand, it is capable of combining the benefits of analytical models and simulation tools (i.e., speed and accuracy). And on the other hand, separating pruning and evaluation phases facilitates the integration of different or additional pruning techniques as well as other existing simulation tools. Finally, we also present several proof-of-concept DSE experiments to illustrate distinct aspects and capabilities of our framework. These experimental results reveal that our approach, compared to other approaches based only on analytical estimation models or simulations guided by e.g. genetic algorithms, not only can explore a large design space and reach a valid solution in a time-efficient way, but also can provide solutions optimizing resource usage efficiency, system traffic and processor load balancing.