The invention discloses a traffic flow prediction method based on a genetic algorithm optimized LSTM neural network. The traffic flow prediction method based on the genetic algorithm optimized LSTM neural network comprises the steps of: S1, acquiring traffic flow data, performing data normalization pre-processing, and dividing the traffic flow data into a training data set and a test data set; S2,predicting various parameters of a model by adopting the genetic algorithm optimized LSTM neural network; S3, inputting genetic algorithm optimized parameters and the training data set, and performing iterative optimization of an LSTM neural network prediction model; and S4, predicting the test data set by using the trained LSTM neural network model, and evaluating the model error. According to the traffic flow prediction method based on the genetic algorithm optimized LSTM neural network in the invention, by utilization of the rapid optimization feature of the genetic algorithm and the LSTMneural network on parameter combination, the relatively high prediction precision can be obtained; furthermore, the method has good applicability on data samples in different intervals; the calculation amount is reduced through the model; and the prediction performance is better.