Based on the algorithm of classification and regression tree (CART (Classification And Regression Tree)) ,a discriminate model of coal and gas outburst was established according to main factors , which are gas pressure ,gas initial velocity ,destructive type of coal ,hard coefficient and depth .Select data of discriminating indexes from typical mines with coal and gas outburst as training data ,and find the champion tree by the method of k‐fold cross‐validated ,then extract the optimized rules ,at lased ,the rules is used to discriminate the coal and gas outburst in the instance .The results show that CART model is a simple and effective method ,it can be used in discriminate analysis of coal and gas outburst as a auxiliary method .%基于分类回归决策树（CART ）算法，考虑影响煤与瓦斯突出的主要因素，建立了煤与瓦斯突出判别的CART模型。模型选择瓦斯压力、瓦斯放散初速度、煤的破坏类型、坚固性系数和垂深作为煤与瓦斯突出的判别指标体系，选取国内典型煤与瓦斯突出矿井的突出数据建立模型样本训练库，利用k‐折交叉验证方法寻找最优树，并提取优化后的突出规则，最后将提取的规则对实例进行验证。研究表明，该模型简单有效，可以作为煤与瓦斯突出判别分析的一种辅助方法。
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