Rapid source identification of mine water inrush has great significance for early warning and rescuing after the mine water inrush. Conventional method taking the concentration of ions as the discriminant factor takes such a long time that a method of rapid source identification of mine water inrush is in urgent need. This method is combined with Laser induced fluorescence (LIF) technology and Partial Least Squares-Discriminant Analysis (PLS-DA) algorithm. In the experiment, 405 nm laser was used to excite the water and 100 groups of fluorescence spectrum from 5 different aquifer of the mine were obtained. According to the spectra curve features, the data was compressed to obtain proper spectral data. 15 groups of spectrum of each water inrush samples were applied, with a total of 75 groups of spectrum as the prediction set while the rest of 25 groups of spectrum as the test set. To verify the experimental result, an experimental model was built with soft independent modeling of class analogy (SIMCA) to compare with PLS-DA. The result shows that the fluorescence spectra of different aquifer water samples is of great difference, without any pre-treatment, the PLS-DA algorithm based on the PLS model has higher modeling accuracy compared with SIMCA algorithm, which reaches to 100%, the validation results and the correlation of separation of variables are both more than 0.951, the RMSECV and RMSEP are both less than 0.123, using the model to identify the 5 water samples of test set, the accuracy are up to 100%.