In order to effectively reduce the casualties and property losses caused by cabin turbulence，a decision analysis method based on a dynamic Bayesian network is proposed for cabin turbulence emergency response. Firstly，according to the relevant laws and regulations at domestic and international，combined with the emergency duties of key personnel on the ground and in the air，the turbulence emergency disposal process is analysed from pre-flight，in-flight and post-flight，and 24 key events are selected to construct a structured BT model. Secondly，the mapping conditions and transformation rules are established to form a DBN model. Then，the objective direct node a priori probability and the supplementary node fuzzy probability obtained by the triangular fuzzy probabilities of supplementary nodes obtained by the fuzzy number expert judgement method to obtain the a priori probabilities of all nodes. Finally，the time slice intervals of 1 and 2 min are selected to focus on the simulation inference of moderate and heavy turbulence，and to study the characteristics of the influence of each dynamic element on the failure of cabin turbulence event disposal. The results show that: the emergency response nodes are significantly affected by the degree of turbulence and time changes，and the optimal time for emergency response is within 5 min. Among them，the probability of failure for the failure of the crew fixation measures in place increases with the increase of the degree of turbulence，human factors such as the failure of the crew to fasten the seat belts and the over-servicing by the cabin crew are the key reasons for the failure of the response.