In view of the shortcomings of the traditional forest precipitation prediction method, a forest precipitation prediction method based on BP neural network optimized by particle swarm algorithm is proposed. Taking the forest precipitation from 2020 to 2022 as a data set for comparative experiments, the experimental results show that compared with the LSTM model and the traditional BP neural network, the PSO-BP neural network algorithm has a significant degree of error reduction and higher prediction accuracy. At the same time, the training set and test set are improved by 5%~11%, which reduces the generalization error and is suitable for forest precipitation prediction with large amount of data. The results show that this method provides a new idea and method for the subsequent forest precipitation prediction.