The changeable weather conditions as well as partial shading situation provide several obstacles in collecting the maximum possible electricity from solar Photovoltaic (PV) systems. The PV system's ability to gather maximum power through maximum power point tracking is hampered mostly by partial shade. In the literature, several MPPT techniques based on bio-inspired optimization approaches have been proposed. These algorithms' procedures vary, causing them to behave differently when assessing global peak power. This work offers a novel Hybrid MPPT model that combines the LSTM algorithm with the Perturb & Observe approach to extract maximum power from photovoltaic fixed overheads in response to variations in solar irradiation and partial shade. LSTM conducts the earliest stages of maximum power point tracking to reach a quicker approximation to the global peak, contributing to the total stage selection of the P & O technique. This method might be effective for mitigating the effects of partial shade. To demonstrate the efficacy of the suggested algorithm in comparison to standard methodologies, 12 hour irradiance characteristics are applied to a solar PV system. MATLAB/SIMULINK software was used to create the suggested MPO-MPPT algorithm-based solar PV system. The system results validate the theoretical analysis of the suggested technique, increasing the PV system tracking efficiency to 97.6%.