Despite significant progress, precipitation forecasting in West Africa remains challenging due to the complexity of atmospheric processes and the region’s climatic variability. This study aims to identify optimal configurations of the WRF model to improve precipitation forecasting. To evaluate the sensitivity of the model’s physical parameterizations, 15 configurations were tested by combining various cumulus parameterization schemes (CPSs) and planetary boundary layer (PBL) schemes. The analysis examines two contrasting rainfall events in Senegal: one characterized by widespread intense precipitation and another featuring localized moderate rainfall. Simulated rainfall, temperature, and humidity were validated against rain gauges, satellite products (ENACTS, ARC2, CHIRPS, and IMERG), and ERA5 reanalysis data. The results show that the WRF configurations achieve correlation coefficients (r) ranging from 0.27 to 0.62 against ENACTS and from 0.15 to 0.41 against rain gauges. The sensitivity analysis reveals that PBL schemes primarily influence temperature and humidity, while CPSs significantly affect precipitation. For the heavy rainfall event, several configurations accurately captured the observed patterns, particularly those using Tiedtke or Grell–Devenyi CPSs coupled with the Mellor–Yamada–Janjic (MYJ) PBL. However, the model showed limited skill in simulating localized convection during the moderate rainfall event. These findings highlight the importance of selecting appropriate parameterizations to enhance WRF-based precipitation forecasting, especially for extreme weather events in West Africa.