Rainfall variability affects rain-fed agriculture, which relies on rainfall. But evidence of sitespecific spatio-temporal rainfall variability and trend remains limited in the study area. Therefore, this study examines the spatio-temporal variability and trends of rainfall in the Upper Central Blue Nile Basin from 1981 to 2024 using the CHIRPS v2 dataset. Coefficient of Variation, Precipitation Concentration Index, Standardized Rainfall Anomaly Index, and Standardized Precipitation Index were used to examine rainfall variability and drought events. Furthermore, the Mann-Kendall, Modified Mann-Kendall test, Sen’s slope estimator, and Innovative Trend Analysis were employed for trend analysis. The Inverse Distance Weighted method was used for spatial analysis in ArcGIS v10.8. The results show highest annual rainfall occurs during the Kiremt season. However, CV values of Belg rainfall indicated greater spatio-temporal variability than Kiremt and annual totals. Also, LGP shows variability over the onset and cessation dates. The PCI results suggest a heterogeneous rainfall distribution in the annual, Kiremt, and Belg seasons. The SRAI result indicates periodic fluctuation of wet and dry years. In addition, SPI values indicated the presence of dry and wet periods with temporal consistency across all study locations in 2015. MK trend test revealed that annual, Kiremt, and Belg rainfall show a significant increasing trend (p<0.05) at 5, 4, and 1 locations with 3.5- 4.1, 2.3-3.7, and 1.3 mm/ year, respectively. The ITA revealed, at the lower cluster, 5 study locations demonstrated a significant upward trend in annual and Kiremt, while downward at Mota in Belg season. At the medium cluster, the majority of locations showed upward trends. In the Belg high cluster, a significant upward trend (p<0.05) was observed in 7 study locations. Therefore, despite insignificant upward trends being dominant, rainfall shows a typical shift and highlights the necessity of localized adaptation measures to protect rain-fed agriculture and improve its resilience in the face of future rainfall variability.