Aiming to effectively evaluate the risk level of the exceeding tire speed rating during take-off of the transport aircraft, and an evaluation model based on cloud model and Bayesian network is proposed. This research selects eight risk indexes, including rotation speed, total weight, low pressure rotor speed, rotation rate, rotation time, elevator control amount, wind component and total air temperature to build the risk index system for exceeding tire speed rating. Then, the cloud model based on heuristic Gaussian cloud transformation algorithm and forward Gaussian cloud algorithm is used to realize the soft classification of exceeding tire speed rating risk level and the discretization of the indexes, and the prior probability of the indexes is calculated. Moreover, the Bayesian network for exceeding tire speed rating risk is constructed, and based on the established network and nodes information, the posterior probability of the said nodes is calculated and the main inducement of exceeding tire speed rating is obtained through network reverse diagnosis. Finally, the simulation experiment has been completed by using the actual operation data from the airlines, and the results show that the evaluation results are consistent with the actual situation, which verify the effectiveness of the model. Therefore, the research can provide theoretical basis for the exceeding tire speed rating analysis and civil aviation takeoff safety risk management.