To establish the optimal predictive model for water inflow in mines, this study is based on the data of water inflow over 650 days at the 1303 working face of the Li Lou Coal Mine. Descriptive statistical graphs are generated to examine the central tendency, dispersion, and distribution of water inflow, along with interpretation based on foundational geological data. The results indicate that the water inflow in the study area exhibits a continuous decrease trend within fluctuations. This feature reflects that the water source for the working face primarily derives from aquifers dominated by static storage and is unrelated to precipitation. Reconstruction parameters were determined based on the C–C method, and phase space reconstruction was conducted. A model was constructed utilizing the weighted first-order local method, resulting in a maximum Lyapunov exponent calculation of 0.24839, with an effective prediction duration of 4 days. Within this effective prediction duration, the average prediction error was 1.74%, indicating good predictive performance; after exceeding the effective prediction duration, the accuracy rapidly decreased, with an average error of 11.12% and a maximum error of 16.13%. These results indicate that applying chaotic methods to short-term prediction of mine water inflow demonstrates high precision, and the predicted outcomes hold practical application value.