This paper describes how MEADEP, a system level dependability prediction tool, and CASRE, a software reliability growth prediction tool can be used together to predict system reliability (probability of failure in a given time interval), availability (proportion of time service is available), and performability (reward-weighted availability). The system includes COTS hardware, COTS software, radar, and communication gateways. The performability metric also accounts for capacity changes as processors in a cluster fail and recover. The Littlewood Verall and Geometric model is used to predict reliability growth from software test data this prediction is integrated into a system level Markov model that incorporates hardware failures and recoveries, redundancy, coverage failures, and capacity. The results of the combined model can be used to predict the contribution of additional testing upon availability and a variety of other figures of merit that support management decisions.