Cloud computing platforms are considerably attractive for parallel applications that perform large-scale, computationally intensive tasks. These platforms can provide elastic computing resources to the parallel software owing to system virtualization technology. Almost every cloud service provider operates on a pay-per-use basis, and therefore, it is important to estimate the performance of parallel applications before deploying them. However, a comprehensive study that can predict the performance of parallel applications remains unexplored and is still a research topic. In this paper, we provide a theoretical performance model that can predict the performance of parallel applications in different virtual machine scheduling policies and evaluate the model in representative hypervisors including KVM, Xen, and VMware. Through this analysis and evaluation, we show that our performance prediction model is accurate and reliable.