The key problems of the seepage flow monitoring of earth-rock dams are how to clarify the influence of water level, rainfall and other factors, how to simulate the real seepage flow and evaluate the results of the seepage monitoring based on the prototype observation. In view of this, a regression model of seepage flow and upstream and downstream water levels is established under the condition of no rainfall using the random forest algorithm and the principles of mathematical statistics. Regarding to the comprehensive influence of the seepage flow on the accumulated rainfall in the earlier period, the Generalized Additive Models for Location, Scale and Shape of Generalized Logistic Distribution (GAMLSS-GLO) is introduced to simulate the fluctuation intervals of the monitoring values of seepage flow under the influence of rainfall. Then, GAMLSS-GLO is superimposed with the seepage flow-water level regression model to predict the reliable intervals of the seepage flow. Finally, the method is applied to the seepage monitoring of the core wall earth-rock dam in Nuozhadu Reservoir. The results show that the proposed method shows good applicability to the water level and rainfall response of seepage flow, it can significantly improve the quality of seepage simulation prediction, and solve the confidence intervals of seepage flow, which is conducive to judging the operation condition and safety monitoring of earth-rock dams.