The surrounding ground settlement in the process of the foundation pit construction is directly related to the safety of the surrounding buildings. In this paper, the ground settlement surrounding the foundation pit was monitored and predicted according to the historical monitoring data, the construction conditions and the surrounding stratum parameters of a foundation pit project in Qiantan district of Shanghai. Based on PSO-BP neural network, this paper compares the network model based on the time series with that based on the settlement influence factors. It is found that the prediction error of these 2 models is small and the prediction precision of neural network based on the time series is higher, which means that PSO-BP neural network can be used to analyze and predict the ground settlement surrounding the foundation pit. In order to comprehensively consider the time effect and space effect, the historical monitoring data is added as the input layer of prediction model for optimization on the basis of prediction model of settlement influencing factors. The results show that the optimized PSO-BP neural network model has a smaller relative error range and a higher prediction precision, and it has good application prospect in the prediction of ground settlement surrounding the foundation pit.