To deeply analyze the influence factors of ship lift deformation, a method for building ship lift deformation monitoring model based on quantile regression is proposed. Based on the structural characteristics of the ship lift, the influence factors such as air temperature and mean value of upstream water level in early stages are introduced into the candidate influence factor set. Adaptive elastic net penalized quantile regression is used for choosing the influence factors of ship lift deformation and building the quantile regression model. The optimal model can be obtained based on the principle of good fitting and validity check. Example verification shows that compared with traditional stepwise regression model, the proposed optimized model has low volatility for prediction accuracy with strong stability, indication a good ability for long term prediction.