Enterprise architecture (EA) is a discipline driving change within organizations. The management of EA change is a challenging task for enterprise architects, due to the complex dependencies amongst EA models when evolving towards different alternatives (To-be models). In this paper, we present an approach supporting design decision during EA evolution. The idea is to reason on (To-be) models when evolving to a posterior state. To that end, we rationalize on a set of design decisions that are

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... pped on a non deterministic finite automaton, which is then evaluated by Markov decision processes. The idea consists of computing EA models valuations while integrating both alternatives rewards and risks metrics. In doing so, we consider risk as a correctness factor to choose the best alternative. Finally, we simulate our risk-based approach using a manufacturing scenario and discuss its usefulness and applicability.