A multi-level coal mine water inrush prediction method based on an SaE-ELM (self-adaptive evolutionary extreme learning machine) includes the steps of 1, researching a coal mine water inrush mechanism and selecting main controlling factors causing coal mine water inrush; 2, searching for a great deal of coal floor water inrush historical data as sample data, with each set of data including main controlling factors and maximum water inrush; 3, dividing the sample data into a training set and a test set, applied to training and testing of a model, respectively; 4, training the sample data with the SaE-ELM to establish a prediction model; 5, testing the prediction model with the data of the test set, comparing obtained prediction results with those obtained by other algorithms; if the prediction precision is high and the speed is high, using the prediction model for predicting whether a coal mine suffers water inrush or not and predicting the degree of water inrush.