<p>Precipitation monitoring is vital for regions like Nigeria, where rainfall variability significantly impacts key sectors, yet conventional rain gauge networks face limitations in spatial coverage. This study conducts a multi-criteria assessment of gridded rainfall data (GRD) accuracy in Nigeria using compromise programming (CP), evaluating eleven free-access gridded precipitation products (FGPPs) against ground observations across daily, monthly, seasonal, and annual scales. The evaluation employs statistical metrics, including Pearson Correlation Coefficient, Mean Error, Bias, Root-Mean-Square Error, and Nash–Sutcliffe Efficiency Coefficient. A multi-criteria evaluation framework using CP was applied to rank the FGPPs based on their reliability across varied temporal resolutions. The study highlights the most reliable datasets for Nigerian applications, enhancing data selection for resource management. This innovative approach ranks the FGPPs in a way that reflects their performance across temporal scales and highlights the most reliable products for Nigerian applications. FGPPs generally demonstrated positive correlations with ground observations, with Global Precipitation Climatology Centre (GPCC), Tropical Applications of Meteorology using SATellite and ground-based observations (TAMSAT) African Rainfall Climatology And Time-series (TARCAT), and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks – Climate Data Record (PERSIANN-CDR) performing well on daily assessments, while Climate Hazards InfraRed Precipitation with Station data (CHIRPS), GPCC, and Global Precipitation Climatology Project (GPCP) as top performers, with observed FGPPs performance varying across eco-climatic regions in Nigeria. Disparities in dataset accuracy highlight the need to select FGPPs adapted to specific temporal and regional conditions, enhancing the accuracy of climate studies and resource management in data-scarce regions.</p>