The data of 65083 cases of upper respiratory tract infection from January 2010 to December 2015 in the No.1 people〖DK〗s Hospital of Jining, Shandong and the data of the meteorological data of the same period are analyzed, and the relationship between upper respiratory tract infection and meteorological factors is studied. According to the actual number of upper respiratory infections, the fullyear is divided into 6 time periods.The meteorological factors with high correlation with upper respiratory tract infection are different in various periods. The stepwise regression analysis method is used to establish the grades forecast equation of upper respiratory tract infection in 6 time periods, and the criteria for classification of forecast grades are determined. The forecast equation is verified with the back substitution method, and the prediction results show that the forecast equation is more accurate for the number of patients with upper respiratory tract infection.