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A reliable fault-tolerant control model for wind turbines (WTs) is a prominent task to meet the control objectives under the presence of the actuator faults. To this aim, the main focus of the present article is the design of a new fault-tolerant control scheme to deal with both additive and multiplicative faults. The design of the proposed method includes two extreme learning machine (ELM) blocks; an ELM-baseline controller to keep the desired wind turbine performances, and fault-tolerant ELM-block to eliminate any possible actuator faults effect. The design process of the ELM controller and the ELM fault estimator are formulated in a way that they only depend on WT input-output data, which allows a much faster and more precise fault tolerance. The effectiveness of the ELM faulttolerant method is tested and compared to a sliding mode observer-based accommodation method using a 5-MW WT benchmark model. Simulation results validate the great performances of the proposed method.