Using global ensemble forecast of European Centre for MediumRange Weather Forecasts (ECMWF) from THORPEX Interactive Grand Global Ensemble (TIGGE) data, and the 24 h observed daily accumulated precipitation data from 20:00 BT to the next 20:00 BT, the applications of the EC ensemble forecast and multiple EC ensemble products and various forecast products of heavy rainfalls by postprocess techniques over Jiangsu Region are evaluated. The results show that the ensemble mean forecast exhibits a high missing forecast rate, and the threat score (TS) is lower than that of EC deterministic forecast. Distinct differences in the forecast skills of each member of EC members and greatly higher TS of the synthesis of the optimal forecasts indicate that the EC ensemble forecast holds great potential application for forecasting heavy rainfall. Multiple postprocess products of ensemble forecast have different performances. Maximum value, the optimal percentage, the frequencymatched based on precipitation forecast bias correction, probabilistic forecasts, ensemble anomaly forecast approach and DuZhou performanceranking method based on the maximum all have higher TS by more than 10%. Then, the TSs of 90% percentage, fusion, the fusionprobability matching and the DuZhou performanceranking method based on the mean or median values are all higher than the EC deterministic forecast. However, the median value and probability matching of EC ensemble forecast are less skillful than ensemble mean with small values in reference. The results of this evaluation may enhance the cognitions of ensemble forecast products and kinds of postprocess techniques, providing forecasters with a useful reference of the utilization of ensemble forecast products for the forecasting of heavy rainfall.