Satellite-based rainfall estimates offer a valuable alternative for rainfall data collection, particularly in developing countries like Malawi, which face challenges due to limited ground gauge station networks. However, these estimates often exhibit biases and systematic errors, necessitating validation against ground station data. The Climate Hazards Group Infrared Precipitation with Station Data (CHIRPS) v2 is one such product that has demonstrated promising performance worldwide and is accessible in Malawi. In this study, we evaluated CHIRPS monthly rainfall estimates from January 1981 to December 2021 against ground station data from twenty locations in Malawi. Our assessment considered CHIRPS' performance in different seasons (wet and dry) and geographic regions (high altitude, medium altitude, low altitude, and the lakeshore). We used both continuous (Coefficient of Correlation (R), Percent Bias (PBias), and unbiased Root Mean Square Error (ubRMSE)) and categorical scores (Probability of Detection (POD), False Alarm Ratio (FAR), and Threat Score (TS)) for evaluation. Our results revealed that CHIRPS outperformed during the wet season in comparison to the dry season, considering both continuous and categorical scores. In terms of geographic locations, CHIRPS exhibited the highest R in the mid-altitude areas during both wet and dry seasons, while low altitude areas had the poorest performance. Additionally, CHIRPS displayed low bias in the mid and low altitude areas during the wet season, with poor performance observed at high altitudes and the lakeshore. In the dry season, mid-altitude areas maintained a good R performance. CHIRPS showed the least error in high altitude areas in both seasons in terms of ubRMSE. Furthermore, all locations achieved a good POD of at least 0.957 during the wet season, while the lakeshore had the highest mean POD of 0.369 during the dry season. All regions exhibited a good FAR during the wet season, with high altitudes performing well in the dry season (mean FAR of 0.250). The Lakeshore reported the highest mean TS of 0.932, while high altitudes had the lowest (mean TS of 0.887). In conclusion, CHIRPS demonstrates superior performance in Malawi during the wet season compared to the dry season. Geographically, there is no single station that excels in all assessments; however, mid- altitude areas consistently perform better in most evaluations. Thus, CHIRPS can be a valuable resource for water management and agricultural operations in Malawi. Keywords:- CHIRPS Dataset; Rainfall Analysis; Seasonal Variability; Geographic Locations; Performance Metrics; Malawi; Satellite-based Estimates; Precipitation Estimation.