Regional groundwater recharge (GWR) is crucial to improving water management strategies; however, the lack of available data constrains its computation. Here, a practical approach using remote sensing data and global hydrological products was implemented to estimate regional GWR in the Basin of Mexico, a ~9,000-km2 basin in central Mexico with a population of ~25 million people, where groundwater represents the most important water source. The soil–water-balance (SWB) model was applied to estimate the regional GWR from 2000 to 2021 in the Basin of Mexico using four model setups, including climatological records from ground stations (M1), remotely based precipitation from CHIRPS (M2), bias-corrected precipitation from CHIRPS (M3), and CHIRPS with temperature from the Daymet product (M4), and other global soil and land use datasets. Furthermore, the regional GWR model was calibrated using runoff from streamflow gauges and evapotranspiration from empirical equations and remote sensing data. The mean regional GWR values estimated in the Basin of Mexico using the M1, M2, M3, and M4 setups were 37, 45, 38, and 45 mm/year (10.38, 12.57, 10.73, 12.61 m3/s), respectively. All setups agreed that the Sierra de las Cruces represents the dominant GWR area; still, larger differences were obtained at high elevations due to the lack of climatological stations. Results suggest that annual precipitation and GWR follow a potential relationship dominated by elevation and surficial lithology. Finally, remote sensing and global sources could be successfully used to depict regional changes in recharge patterns within data-limited basins.