Abstract: Based on the number of influenza cases amongst preschool children and meteorological observations over Beijing-Tianjin-Hebei area from 2014 to 2016, the relationships between the incidence of preschool children influenza and individual meteorological factor as well as their combined conditions are investigated. The results indicate significant linear correlations between the number of influenza infection amongst preschool children and temperature, relative humidity, atmospheric pressure and a defined comprehensive indicator Body Perception Weather Index (BPWI). The exposure-consequence relationship based on the BPWI is more stable, i.e., while the BPWI values equal or smaller than −11 or within the range of 0—10 correspond to higher risk of influenza. Local atmospheric pressure is another key factor. When the station pressure is higher than 905 hPa, higher pressure causes more infection, and the infection peak corresponds to 1007 hPa. On the basis of these understanding, a machine learning method is used to perform prediction experiment, and it is found that the BPWI with a 3 d lead time contributes the most to influenza incidence. The hindcast evaluation reports a fairly good performance of the prediction model, and this provides valuable evidences and scientific clues for pre-intervention.