The invention belongs to the technical field of deposit hydrogeological exploration and relates to a water inflow forecasting method based on wavelet transform and ARMA-SVM (auto-regressive moving-average model-support vector machine). The water inflow forecasting method comprises the following steps: collecting and analyzing the water inflow account data of a mine, then selecting a modeling sample and an inspection sample, performing dyadic wavelet decomposition and reconstruction on the modeling sample, extracting a high-frequency signal and a low-frequency signal in an original time sequence, utilizing the ARMA model to build a high-frequency signal model, meanwhile, utilizing the SVM to build a low-frequency signal model, synthesizing the high-frequency signal model and the low-frequency signal model to obtain a final water inflow prediction model, and finally, utilizing the inspection sample to inspect the final prediction model to realize water inflow prediction. While the low-frequency signal is fully fit, over-fitting of the high-frequency signal is avoided, the working principle is reliable, the prediction method is simple, the prediction precision is high and the prediction environment is friendly.