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Event-based communication is used in different domains including telecommunications, transportation, and business information systems to build scalable distributed systems. Such systems typically have stringent requirements for performance and scalability as they provide business and mission critical services. While the use of event-based communication enables loosely-coupled interactions between components and leads to improved system scalability, it makes it much harder for developers to estimate the system's behavior and performance under load due to the decoupling of components and control flow. In this paper, we present our approach enabling the modeling and performance prediction of event-based systems at the architecture level. Applying a model-to-model transformation, our approach integrates platform-specific performance influences of the underlying middleware while enabling the use of different existing analytical and simulation-based prediction techniques. In summary, the contributions of this paper are: (1) the development of a meta-model for event-based communication at the architecture level, (2) a platform aware model-to-model transformation, and (3) a detailed evaluation of the applicability of our approach based on two representative real-world case studies. The results demonstrate the effectiveness, practicability and accuracy of the proposed modeling and prediction approach. [ABSTRACT FROM AUTHOR]