With the global climate change, drought disasters occur frequently. Drought prediction is an important content for drought disaster management, planning and management of water resource systems of a river basin. In this study, a short-term drought prediction model based on deep belief networks (DBNs) is proposed to predict the time series of different time-scale standardized precipitation index (SPI). The DBN model is applied to predict the drought time series in the Huaihe River Basin, China. Compared with BP neural network, the DBN-based drought prediction model has shown better predictive skills than the BP neural network for the different time-scale SPI. This research can improve drought prediction technology and be helpful for water resources managers and decision makers in managing drought disasters.