This study proposed a building energy consumption prediction method based on Q-learning algorithm. By modeling the building energy consumption prediction problem as a standard Markov decision process, combining with the deep belief network to model the state, we use Q-learning algorithm to achieve the real-time prediction of the building energy consumption. Based on the building energy consumption data published by Baltimore Gas and Electric Power Company of the United States, the proposed model were tested and the results show that the Q-learning algorithm can be used to predict the building energy consumption successfully. Moreover, deep belief network can improve the prediction accuracy effectively. In addition, some experimental results further verify the influence of related parameters on experimental performance.