Abstract. This study analyzes extensive data sets collected during the twentieth century and defines four modes of natural variability in the flow of the Nile River, identifying a new significant potential for improving predictability of floods and droughts. Previous studies have identified a significant teleconnection between the Nile flow and the eastern Pacific Ocean. El Niño–Southern Oscillation (ENSO) explains about 25% of the interannual variability in the Nile flow. Here, this study identifies a region in the southern Indian Ocean, with a similarly strong teleconnection to the Nile flow. Sea surface temperature (SST) in the region (50–80° E and 25–35° S) explains 28% of the interannual variability in the flow of the Nile River and, when combined with the ENSO index, the explained variability of the flow of the Nile River increases to 44%. In addition, during those years with anomalous SST conditions in both oceans, this study estimates that indices of the SSTs in the Pacific and Indian oceans can collectively explain up to 84% of the interannual variability in the flow of the Nile. Building on these findings, this study uses the classical Bayesian theorem to develop a new hybrid forecasting algorithm that predicts the Nile flow based on global model predictions of indices of the SST in the eastern Pacific and southern Indian oceans.