Aiming at the problem of poor prediction accuracy of traditional deformation statistical model and BP neural network model, this paper discussed the horizontal displacement prediction of BP neural network-weighted Markov model. First, the mean-mean square error method was used to classify the relative error sequence fitted by the BP neural network and to check the Markovity of the state sequence. Then, the autocorrelation coefficients and weights of each order were calculated, and the weighted and maximum probability values were used to predict the future random state. Finally, taking the measured horizontal displacement of the Gate Pier 11 of Wangfuzhou Water Control Project as an example, the prediction results of the stepwise regression statistical model, BP neural network model and BP neural network-weighted Markov model were compared. The results show that compared to the stepwise regression statistical model and BP neural network model, the BP neural network-weighted Markov model has higher prediction accuracy, which indicates that this model is more reliable.