Abstract: The research on the technical methods of soybean climate quality assessment is not only an inevitable requirement for the development of agricultural product climate quality certification services, but also a realistic requirement for planting structure adjustment in Heilongjiang Province. In this paper, the soybean growth period, yield, meteorological disasters, and meteorological data such as temperature, precipitation and sunshine in Huma County from 1981 to 2018 were used to study and determine the technical indicators for soybean climate quality evaluation, and an evaluation model was established. Six key impact factors for soybean climate quality assessment (annual≥10℃ accumulated temperature, flowering period low temperature, flowering period sunshine, flowering period precipitation, pod blast stage precipitation, initial frost) and grading indicators were determined. By comparing and analyzing the expert scoring method, correlation coefficient method and path coefficient method, the correlation coefficient method was used to determine the weight coefficient to establish the soybean climate quality evaluation model. The historical fitting accuracy rate reached 88%, indicating that the method has High practicality.