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In this paper, we suggest a framework for determining the best operation and maintenance strategies for offshore wind turbines. The framework takes into account both quantitative and qualitative data gathered from the wind turbines. The proposed framework consists of a simulation‐optimization approach for designing, planning, and scheduling maintenance operations for offshore wind farms and finding the optimal intervention solution for minimizing costs while keeping a high availability of wind turbines and guaranteeing safety standards for workers. Several parameters and constraints are addressed to account for the realistic complexity of the problem, such as weather conditions, resource cost, and maintenance duration. A numerical case study focusing on offshore wind turbine blade maintenance is presented to demonstrate the implementation of the proposed framework. The example simulates realistic defect progression scenarios, stratified by severity level, and incorporates empirically grounded estimates of failure rates, repair costs, technician requirements, and vessel logistics. The study illustrates how the simulation‐optimization approach integrates economic considerations, resource constraints, and safety risk factors to support data‐informed maintenance scheduling decisions under uncertainty.