In order to gain an in-depth understanding of the microseismic activity characteristics of a lead-zinc-sulfur iron mine as a whole, and avoid the situation where it is difficult to describe the complex information contained in the rock instability process using a single indicator during microseismic monitoring, this paper selects the ratio of energy to apparent volume, cumulative microseismic count, microseismic activity βn, regional concentration, and η value as characteristic parameters for grey correlation analysis and combines entropy weight method to find that the cumulative number of microseismic events and the ratio of energy to apparent volume EEI have an important influence on the formation of ground pressure disasters. The ground pressure risk during each monitoring period is scored using grey comprehensive evaluation, establishing an early warning and prediction model that can be continuously improved as more microseismic monitoring data becomes available and performing well in subsequent monitoring work