Electric power is crucial for driving the progress of any nation, because of the accumulative demand for power production worldwide. In this regard, conventional energy sources (CES) are depleting and emitting greenhouse gases into the environment. Therefore, renewable energy sources (RES) are the best option for meeting the required clean power generation. This paper introduces a novel neural network (NN)-based MPPT technique for optimizing the power generation of wind turbine (WT) framework management under variable environmental conditions. The proposed framework effectively captures the complex relationship between WS, turbine parameters, and power output, enabling specific tracking of the MPP. The proposed approach is simulated in MATLAB/Simulink and performs better than conventional specified MPPT algorithms. This results in enhanced energy extraction and improved system efficiency of the WT module.