Abstract: Land subsidence is an environmental geological phenomenon caused by many factors, and it can reduce the smoothness of high-speed railways and thus affects the safe operation of high-speed railways. Traditional rardom forest models do not take account of the internal complexity of time series data in the prediction of time series data. Therefore, this paper constructs a wavelet transform-random forest (WT-RF) prediction model, predicts the land subsidence along the Tianjin-Baoding high-speed railway using the model, and assesses the impacts of land subsidence on the changes in the slope of the high-speed railway. The results are as follows: ① From 2016 to 2018, the change range of the slope of the Tianjin-Baoding high-speed railway was 0~0.16‰ due to the cumulative land subsidence. ② The WT-RF model showed high prediction accuracy of the land subsidence. ③ From 2018 to 2020, the land subsidence still showed an increasing trend, although the change range of the slope along the Tianjin-Baoding high-speed railway was 0~0.2 ‰. It can be concluded that the land subsidence has an impact on the changes in the slope of the Tianjin-Baoding high-speed railway. Therefore, it is necessary to control the land subsidence to ensure the safe operation of the high-speed railway.