For the multi-parameter, nonlinear, and real-time problem in air combat situation assessment, an approach is proposed based on a novel structure of decision tree. Ensuring the basis for the assessment of the situation includes obtaining the information of the warring parties and the state parameters of the unmanned aerial vehicle(UAV). The enemy was used as the input of the decision tree and four kinds of situation results as the output of the decision tree, which provided a theoretical basis for the rationality of the result of the UAV situation estimation. According to the state parameters that affect the attack area of the air-to-air missile, by comparing the same state parameters, the magnitude of the evaluation index value of the UAV and the enemy aircraft were obtained, and the corresponding indicators of the air combat situation classification were designed to meet the rapid response requirements of the situation assessment. The rules of the air combat situation classification were established to be inference rules of the decision tree. Finally, anti-reasoning rules were proposed for undeveloped branches in the decision tree in order to improve learning under unknown conditions. Extensive simulations, including one-to-one, one-to-two, and two-to-two air combat scenarios, show that the computing time of the proposed method was 5.39 s and its accuracy was 80%, while the computing time of the Bayesian was 11.63 s and the accuracy was 60%. The results indicate that the proposed optimal method has faster assessment speed and higher accuracy than the traditional Bayesian network.