For the energy market, accurate prediction of energy prices plays a very important role for investors, consumers and governments. However, traditional energy price forecasts generally have problems such as low accuracy, low efficiency, and insufficient stability. In response to these problems, this article uses neural networks to analyze energy price predictions. The study found that the energy price prediction model based on BP neural network can accurately predict energy prices, and the minimum error can reach 2%. In addition, BP neural network also has the advantages of high efficiency and high stability in the energy price prediction process.