The invention discloses a frequent item set mining method for game prop recommendation and belongs to the technical field of data mining. The frequent item set mining method comprises the following steps: firstly, acquiring occurrence times of each item on MapReduce, performing sequencing and threshold screening to reject unqualified items and obtain F-List, dividing the F-List so as to obtain G-List, according to division of G-List, transmitting data to Mapper, performing Mapper processing, transmitting data to Reducer, and performing MapReduce mining on the Reducer; and for mining, firstly acquiring PPCTree on each Reducer, after PPCTree is obtained, acquiring L-List and G-Subsume of corresponding items on each Reducer, and finally performing recursion according to the N-List and the G-Subsume, thereby obtaining a final frequent item set. By adopting the frequent item set mining method, the data is reasonably divided according to load prediction, and thus load balance can be ensured; and as the recursion mining process is optimized, the dense data mining time can be greatly shortened.