The basic principle of generalized linear models(GLM) was used in risk assessment method. The cumulative occurrence probability of the risk was transformed into logistic form according to its level. The risk assessment regression model was founded based on the prior information of the samples taking the transformed cumulative probability as the linking function. Then every level's cumulative occurrence probabilities of the risks assessed were gained using the founded regression model and the occurrence probability was calculated. The final risk level was determined with the level of maximum occurrence probability. The coefficients of the regression model were estimated with MLE and calculated by Newton-Raphson iterative algorithm, and the goodness of fit of the model was tested by Pearson x2 test. The method was applied in coal and gas outburst risk evaluation and a specific mine was assessed. The results show that this method is accurate and valuable.%应用广义线性模型处理风险评价中响应变量为属性变量或离散型变量的问题，对风险事件依风险等级的累计发生概率进行logistic变换，以变换的累计发生概率作为连接函数，基于风险样本事件先验信息建立回归模型。针对待评价的风险事件，利用所建立的回归模型分别计算各风险等级的累计发生概率和发生概率，以其最大发生概率所对应的等级作为风险事件的最终评价等级。在建模过程中，采用极大似然估计法对回归系数进行参数估计并采用Newton-Raphson迭代算法求解，模型的拟合优度采用皮尔逊X2检验。应用本方法建立煤与瓦斯突出的概率风险评价模型，并对具体矿井煤与瓦斯突出的概率风险进行评价。研究结果表明：采用该方法可准确得出评价结果。
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