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This article presents an integrated multistate method for the early-phase design of inherently robust systems; namely, those capable, as a prima facie quality, of maintaining adequate performance in the face of probabilistic system events or failures. The methodology merges integrated multidisciplinary analysis techniques for system design with behavioral-Markov analysis methods used to define probabilistic metrics such as reliability and availability. The result is a multistate approach that concurrently manipulates design variables and component failure rates to better identify key features for an inherently robust system. This methodology is demonstrated on the design of a long-endurance unmanned aerial vehicle for a three-month ice surveillance mission over Antarctica. The vehicle is designed using the multistate methodology and then compared to a baseline design created for the best performance under nominal conditions. Results demonstrated an improvement of 10–11% in system availability over this period with minimal impacts on cost or performance.