Accurate prediction of heavy rainfall events poses a significant challenge in numerical weather prediction (NWP) due to the complex processes in the atmosphere, its dynamic behavior, the parameterization of microphysical processes, and model uncertainties. In recent decades, Egypt has experienced extreme precipitation events, particularly along its northern coast, some of which exceeded expected intensity levels. This study aims to enhance the prediction of extreme rainfall events over Egypt using the ICTP regional climate model version 5 (RegCM5). We tested various convective schemes within the following models: Emanuel (1991), Grell (1993) with the Fritsch–Chappell (1980) cumulus closure scheme, Kain–Fritsch (1990), and Tiedtke (1996), to identify the optimal schemes that capture the different rainfall cases. For our experiments, we utilized the ERA5 and FNL reanalysis datasets as the initial and boundary conditions (ICBC) for RegCM5. All simulations were conducted with a spatial resolution of 5 km. To verify our results, we compared the simulated rainfall with the measurements from four ground stations in Alexandria (El-Nouzha, Abu-Qir, Borg El-Arab, and Ras El-Tin), in addition to the precipitation data from the ERA5 reanalysis, CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data), GPM, and the PERSIANN-Cloud Classification System (PERSIANN-CCS). Based on comparisons between the simulated precipitation from RegCM5 and data from the four rain gauges, the Kain–Fritsch scheme demonstrated both high performance and low mean bias error (MBE), followed closely by the Grell scheme.