Abstract: In order to solve the uncertainty and randomness in the process of mining safety production accident prediction, a fuzzy interval prediction model of mining safety production accident time series was proposed. Wavelet transform was used to decompose the time series of mining safety production accidents into a set of high-frequency signal sequences and a set of low-frequency signal sequences, sample entropy was used to reconstruct the subsequence, and it was mapped to windowed time series with three parameters of Low, R and Up parameters; Fuzzy C-means clustering (FCM) algorithm was used to predict the windowed time series, the interval prediction results of the mining safety production accident time series were obtained, and 6 sets of test samples were used to verify the prediction accuracy of the model. The results show that the average relative errors of R value and Up value are 17.737 1% and 8.771 2% respectively, indicating that the fuzzy interval prediction model of mining safety production accident time series has high accuracy and reasonable interval range, which can provide theoretical basis for mining safety decision-making.