Abstract: Based on the daily precipitation data of 622 stations,the change and trend predictions of extreme precipitation events in China are explored by using the Mann-Kendall test,Sen’s slope,R/S analysis and other methods. The results show that:（1） Over the past 60 years,the extreme precipitation index in China has shown a no significant increase（p＞0.05）,and the maximum day precipitation（RX1day）,the maximum five-day precipitation（RX5day）,the heavy precipitation（R95p）and the total precipitation（PRCPTOT）have increased by0.52,0.10,0.64 and 6.00 mm/10 a,respectively. The extreme precipitation intensity index（SDII）increased significantly at a rate of 0.13（mm/d）/10 a（p＜0.05）,while the extreme precipitation day index shows no significant increase（p＞0.05）,with R20 and R50 increasing at rates of 0.13 and 0.06 d/10 a,respectively.（2） From the perspective of different regions,in addition to continuous wet days（CWD）,other indices of extreme precipitation events show a significant increase in Southern,Central,Northwest and Southwest China（p＜0.05）,and a significant decrease in Northeast and Northern China（p＜0.05）. Thereinto,the increase rates of RX1day are 0.62,0.52,0.21 and 0.49 mm/10 a in Southern,Central,Northwest and Southwest China,respectively. The decrease rates of RX1day are-0.48 and-0.63 mm/10 a in Northeast and Northern China,respectively. Outside of Southern China,CWD decreases significantly at rates below 0.05 d/10 a（p＜0.05）.（3） In addition to R95p and PRCPTOT,other extreme precipitation indexes will continue their historical trend in the future（H＞0.5）. Both the extreme precipitation index and the extreme precipitation intensity index will show a sustained growth trend,and the significant increase will continue in Southern,Central,Northwest and Southwest China. Although the extreme precipitation daily index is generally an upward trend,the CWD will still show a strong downward outside southern China. The results can provide a reference for rainstorm disaster warnings and regional water resource utilization in China.