Airport resilience is reflected in the airport 's ability to adapt to environmental changes, have strong resistance and achieve performance recovery. Based on the level of airport performance, this paper puts forward the calculation formula and evaluation standard of airport resilience index to reflect the level of airport resilience. Considering the level of meteorological disasters and the strength of airport prevention and recovery measures, an airport performance level calculation model based on dynamic Bayesian network is established. The conditional probability table between Bayesian network nodes is established by the parent node level index and the node state transition performance. The fuzzy theory is used to improve and calculate the airport resilience index and sub characteristic index. Taking Tianjin Binhai International Airport as an example, the evaluation results of airport resilience under blizzard in February 2021 are obtained, and the validity of the model is verified based on real flight data. The results show that compared with the performance level calculation method based on flight data, the calculation error of airport resilience index of dynamic Bayesian network model proposed in this paper is less than 0.01, and the average error of sub-characteristics is 0.0129, which can scientifically and accurately evaluate the resilience of airport during normal operation and the dynamic change process of resilience under disaster. The influence of disaster level, prevention and recovery measures on airport resilience is further analyzed. The results show that the deterioration effect of disaster on airport resilience is greater than the resistance effect of prevention measures. The higher the disaster level and the lower the level of preventive measures, the smaller the degree of resilience recovery of the airport.