Based on the refined numerical prediction products of the European Center of Medium-range Weather Forecast (ECMWF), precipitation guidance products from China Meteorological Administration (TP_CMA) and precipitation observation data at 340 meteorological stations of Gansu Province, the objective divisions of precipitation at 340 meteorological stations of Gansu Province from April to September during 2017-2019 were done by using spatial cluster and Tyson polygon (SCTP) approach. On this basis, the physical quantity factors related to precipitation were selected and used to build prediction model by using random forest (RF) algorithm, and the correction experiment of short-term quantitative precipitation objective forecast in Gansu Province was carried out, the forecast effect was verified. The results are as follows: (1) There were 7, 6, 14, 13, 14 and 11 precipitation regions in sequence from April to September in Gansu Province. (2) In terms of rain probability forecast, the forecast ability of SCTP-RF products in flood season (from June to August) in Gansu Province was better than that of TP_CMA guidance products and ECMWF model products, and the prediction accuracy improved by 6.1% and 4.2%, respectively. In space, SCTP-RF products had a certain ability to correct rain probability forecast at all stations of Gansu Province, and the prediction accuracy at most stations improved by 5%, especially in the east of Yellow River in Gansu (Hedong area). (3) For graded precipitation forecast, the forecast ability of SCTP-RF products to moderate rain and heavy rain was superior to TP_CMA guidance products and ECMWF model products, and the correction effect at most stations was better, especially in the middle part of Hedong and southeastern Gansu. However, the correction ability to light rain and rainstorm forecast was unstable during the heavy rainfall processes, especially to light rain in southeastern Gansu.