Abstract: Enterprise storage systems depend on disk arrays for their capacity and availability needs. To design and maintain storage systems that efficiently satisfy evolving requirements, it is critical to be able to evaluate configuration alternatives without having to physically implement them. In this paper, we describe an analytical model to predict disk array throughput, based on a hierarchical decomposition of the internal array architecture. We validate the model against a state-of-the-art disk array for a variety of synthetic workloads and array configurations. To our knowledge, no previously published analytical model has either incorporated the combined effects of the complex optimizations present in modern disk arrays, or been validated against a real, commercial array. Our results are quite encouraging for an analytical model: predictions are accurate in most cases within 32% of the observed array performance (15% on the average) for our set of experiments.