One of the most prevalent difficulties in PV systems is partial shading condition (PSC), which results in considerable de-creases in energy production. Even so, this can create multiple lo-cal maximum power points (MPP) (in the PV curve) and can cause conventional and advanced Maximum Power Point Tracking (MPPT) controllers to operate the PV system at a low peak value. Consequently, the PV system's power output is reduced further. By incorporating a global MPP searching method in the MPPT controller, the PV system can operate at its greatest efficiency under PSC. This paper proposes a global MPP (GMPP) method based on Bald Eagle Searching (BES), which finds the maximum value in three stages (selecting space, searching in space, and swooping). This study uses the first stage of the BES method to design the proposed GMPP searching method. The BES method demonstrates better performance than Cuckoo Search (CS) and Particle Swarm Optimization (PSO). Compared with the PSO and CS methods, the proposed method reduces search time (average of all PSC cases) by 36.17% and 40.76%, respectively. Further-more, it finds the GMPP in all simulated PSC cases without fail. In addition to its excellent performance, the proposed method is simple and easy to implement due to its single tuning parameter, unlike PSO and CS.