We introduce a new performance evaluation methodology that helps programmers evaluate different tuning alternatives in order to improve program performance. This methodology permits measuring performance implications of using tuning alternatives. Specifically, the methodology predicts performance after workload migration for a distributed or parallel program in contrast to traditional performance methodlogies that quantify time spent in program components for bottleneck identification. The methodology thus provides guidance on workload migration. The methodology also permits predicting the performance impact of changing the underlying network. The methodology may evaluate performance incrementally and online during the execution of the program to be tuned. We show that our methodology, when it is implemented and used, permits accurately predicting the performance of different tuning alternatives for a test suite of six programs.