DescriptionPerformance modeling of complex and large processing systems containing multiple processors, shared memories and multiple application threads remain inadequate. Conventional modeling approach to predict performance early in architecture phase relies on modeling methodology utilizing languages like SystemC are complex and yet yield inaccurate performance data. This paper proposes tools and methodology for architecture modeling and performance analysis by adopting data flow approach. The modeling approach decouples functionalities and timings thereby significantly reducing complexity. Instead of executing functionally correct software, it performs statistical analysis of software instructions. Besides predicting performance, the model also provides high confidence hardware and software design constraints.