Climate warming has led to more frequent and stronger extreme precipitation events in Central Asia (CA) in recent decades, which has seriously affected local socio-economic development and agricultural production. Based on the numerical simulations provided by the latest 14 coupled models of the Sixth Phase of Coupled Model Intercomparison Project (CMIP6), this study predicts and studies the spatial and temporal distribution characteristics of extreme precipitation over CA and its relationship with regional climate warming in the middle and late 21st century under two shared socio-economic paths (SSP2-4.5 and SSP5-8.5). The results show that most CMIP6 models can basically simulate the spatial distribution characteristics of observed precipitation climate states for 1979-2018, but the model simulations underestimate the observations in the southwest and southeast of CA, and overestimate the observations in the north and Central South of CA. Compared with the historical period (1981-2010), the precipitation intensity at the end of the 21st century (2071-2100) increased by 0.54 mm/10a and 2.4 mm/10a under the scenarios of SSP2-4.5 and SSP5-8.5 respectively, while the frequency of extreme precipitation events increased by 5-7% and 6-10% respectively, especially in the high-altitude mountains in central and southern regions. The signal-to-noise ratio (SNR) of the predicted precipitation intensity and frequency in northeast Central Asia to the north of The Tianshan Mountains is more reliable. Climate warming has an obvious regulatory effect on the frequency of extreme precipitation events in CA in the future. For the temperature rises by 1K, the frequency of extreme heavy precipitation events increased by about 7and 9 days, while the maximum continuous dry days increased by 3 and 6 days, respectively.