The invention discloses a crowd trajectory prediction method and system based on a deep convolutional long and short memory network. The method comprises the steps of firstly determining a pedestriantrajectory data set; secondly, determining a training set and a test set according to the pedestrian trajectory data set; constructing a Conv-LSTM model of the deep convolution long-short term memorynetwork again; determining parameters of a deep Conv-LSTM model according to a training set and the test set; and finally, performing crowd trajectory prediction according to the deep Conv-LSTM modelwith the parameters. According to the method, a Conv-LSTM (Convolutional Long Short Term Memory) model of the deep convolution long-short term memory network is constructed; a deep Conv-LSTM model isused to carry out crowd trajectory prediction; on one hand, the complexity of the network and the prediction precision of the crowd trajectory are improved, the time and space memory of the network for the historical trajectory of the crowd is deepened, and on the other hand, the regression capability of the network is further improved by adopting the context semantic space information output by the convolutional network for the Conv-LSTM layer.