Designing storage systems to provide business continuity in the face of failures requires the use of various data protection techniques, such as backup, remote mirroring, point-in-time copies and vaulting, often in concert. Predicting the dependability provided by such compositions of techniques is difficult, yet necessary for dependable system design. We present a framework for evaluating the dependability of data storage systems, including both individual data protection techniques and their compositions. Our models estimate storage system recovery time, data loss, normal mode system utilization and operational costs under a variety of failure scenarios. We demonstrate the effectiveness of these modeling techniques through a case study using real-world storage system designs and workloads.