This research evaluated the applicability of monthly Satellite-based and Reanalyzed Precipitation Products (SRPPs) for drought monitoring in the Khorasan Razavi region northeast of Iran. The study compares four monthly averaged SRPPs freely available on Google Earth Engine (GEE), namely the Tropical Rainfall Measuring Mission (TRMM), Global Precipitation Measurement (GPM), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), and ECMWF Re-Analysis version 5 (ERA5), to the long-term monthly observed precipitation data (1987-2020) in terms of systematic bias and skill. The model performance was assessed using various evaluation metrics and graphical visualizations. The results indicated that TRMM3b43-v7 and GPM-IMERG products outperformed ERA5 and PERSIANN-CDR in detecting drought events. This study highlights the potential of GPM-IMERG and TRMM3b43-v7 products for drought analysis, offering an alternative framework for future research in climate, hydrology, and drought studies, particularly in regions with limited observation data. However, it is worth noting that the satellite-derived Standardized Precipitation Index (SPI) is highly time-dependent and does not yield consistent results throughout the year. Addressing this issue requires more advanced technology and sophisticated algorithms to navigate the complexities of air masses globally.