Most existing dependability modeling and evaluation tools are designed for building and solving commonly used models with emphasis on solution techniques, not for identifying realistic models from measurements. In this paper, a measurement-based dependability analysis package, MEASURE+, is introduced. Given measured data from real systems in a specified format, MEASURE+ can generate appropriate dependability models and measures including Markov and semi-Markov models, fc-out-of-n availability models, failure distribution and hazard functions, and correlation parameters. These models and measures obtained from data are valuable for understanding actual error/failure characteristics, identifying system bottlenecks, evaluating dependability for real systems, and verifying assumptions made in analytical models. The paper illustrates MEASURE+ by applying it to the data from a VAXcluster multicomputer system. Models of field failure behavior identified by MEASURE+ indicate that both traditional models assuming failure independence and those few taking correlation into account are not representative of the actual occurrence process of correlated failures.