Land Use and Land Cover (LULC) changes significantly influence flood hazard, especially in rapidly urbanizing areas like the Wadi Ibrahim watershed in Makkah, Saudi Arabia. This study analyzed the impacts of historical (2001-2025) and projected (2037) LULC changes on floods using remote sensing, GIS, and hydrological modeling with 30 m DEM and Landsat data. Urban growth was assessed from 2001, 2013, and 2025 maps, and future scenarios were simulated with the MOLUSCE plugin in QGIS using Cellular Automata-Artificial Neural Network (CA-ANN) techniques. Hydrological simulations were used to examine changes in flood discharge and response to LULC transitions. The results revealed substantial urban expansion, with built-up areas increasing from 12 km2 (11%) in 2001 to 28.7 km2 (26%) in 2025 and projected to reach 31.9 km2 (28.3%) by 2037. The corresponding impervious surface fraction rose from 11% to 28% over the same period. Hydrological modeling for 50-, 100-, and 200-year return periods reveals a significant escalation in flood response, with peak discharge (Qp) increasing by up to 12% and runoff volume (V) by approximately 9% between 2001 and 2037. The LULC classification using the Random Forest algorithm demonstrated strong and reliable performance, achieving an average Kappa (kappa) value of 0.86, indicating almost perfect agreement. Overall, the findings underscore the need for sustainable land management to reduce flood risk in rapidly growing arid regions.