The prevalence and severity of pollen-induced pollinosis has been increasing yearly worldwide in recent years. Pollen is the main allergen causing allergic rhinitis in North China and the onset period of airborne allergenic pollen-induced pollinosis coincides with the peak period of pollen concentration. As one of the mega-cities in the northern region of China, Beijing is becoming increasingly aware of the problems caused by allergenic pollen. Based on the analysis of 12 pollen sampling stations daily classified pollen concentration observation data during pollen season in Beijing from 2012 to 2020, there were two peak periods of pollen concentration in Beijing from early March to mid-May (it could be further divided into two peak periods from mid-March to early April and from late April to early May) and from mid-August to mid-September, respectively. The dominant allergenic pollen species in the first peak period were Cupressaceae, Salicaceae (from early March to mid-April, the annual average concentration accounted for 39.1% and 18.2% respectively) and Pinaceae (from mid-April to early May, the annual average concentration accounted for 18.2%), and the dominant allergenic pollen species in the second peak period were Moraceae, Artemisia and Chenopodiaceae (from mid-August to mid-September, the annual average concentration accounted for 34.4%, 30.4% and 12.7% respectively). The annual maximum concentration of dominant airborne allergenic pollen in Beijing varied significantly among stations and pollen seasons, and fluctuated significantly. In contrast, the variation of the dates of annual maximum pollen concentration of the same species is relatively stable, and its prediction research work is more meaningful for pollen-induced pollinosis control. Based on the observation data of annual maximum concentration of dominant airborne allergenic pollen and the cumulative value of daily meteorological observation data matched with the location of pollen sampling stations, a prediction model of date of annual maximum concentration of main airborne allergenic pollen in Beijing is established based on the principle of crop growth model and fuzzy logic. The results showed that the prediction accuracy of pollen models of Cupressaceae, Salicaceae, Pinaceae, Moraceae, Artemisia and Chenopodiaceae were 87.8%, 80.0%, 64.4%, 86.7%, 78.8% and 81.8%, respectively. Using a model based on fuzzy logic principle and driven by the cumulative values of daily meteorological elements for pollen annual maximum concentration date, combined with the high-resolution regional numerical weather prediction model in Beijing, we can make a reasonable prediction of the time of maximum pollen concentration of different airborne allergenic pollens and provide a theoretical reference for the prevention and control of local airborne allergenic pollen-induced pollinosis.