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从随机理论与滑坡学相交叉的角度，论述了概率理论和方法在斜坡稳定性研究中的应用。构造了概率滑坡学的基本框架和主要内容。根据国内外最新研究文献及作者的研究成果，系统总结了斜坡稳定性评价中的概率理论和方法，并配有研究实例，突出其实用性和可操作性。主要内容为：论述了斜坡系统的复杂性、不确定性和相关性，指出了传统安全系数方法的缺陷和引入概率方法的必要性。给出了强度参数的变异性和相关性对斜坡系统的可靠度影响。系统介绍和总结了可靠性理论在斜坡稳定性分析中的基本原理、方法。主要包括模拟实验的ＭｏｎｔｅＣａｒｌｏ模拟方法，近似概率方法的一次二阶矩法（ＦＯＳＭ），统计矩法（Ｒｏｓｅｎｂｌｕｅｔｈ）。详述了这些方法的计算步骤、应用条件和实例分析。在斜坡的可靠性分析中，引入了函数连分式渐近法，其特点是计算速度快、简捷、精度高，有效地将斜坡稳定性评价的定值方法和概率方法有机地相结合。简介了随机有限元方法、最大熵密度函数法，马氏链方法。对上述的主要方法应用同一实例进行对比研究，结果相近，结论一致。论述了空间预测预报的理论基础。对比研究了信息量法和回归分析，结果较吻合。根据破坏概率数值区间（０，０．３），（０．３，０．５），（０．５，０?
From the perspective of stochastic theory and landslide, the application of probability theory and method in slope stability research is discussed. The basic framework and main contents of probabilistic landslide are constructed. According to the latest research literature at home and abroad and the author’s research results, the probability theory and method in slope stability evaluation are systematically summarized, and examples are given to highlight the practicality and operability. The main contents are as follows: The complexity, uncertainty and relativity of slope system are discussed. The defects of traditional safety factor method and the necessity of introducing probability method are pointed out. The influence of the variability and correlation of the intensity parameters on the reliability of the slope system is given. The system introduces and summarizes the basic theory and method of reliability theory in slope stability analysis. It mainly includes MonteCarlo simulation method of simulation experiment, first order second moment method (FOSM) and Rosenblueth method of approximate probability method. The calculation steps, application conditions and case studies of these methods are described in detail. In the reliability analysis of slopes, the function continuous fraction asymptotic method is introduced, which is characterized by fast calculation speed, simple and high precision, and effectively combines the fixed value method and probabilistic method of slope stability evaluation. This paper introduces the stochastic finite element method, the maximum entropy density function method and the Markov chain method. The main method of the above application of the same example for comparative study, the results are similar, the conclusion is consistent. The theoretical basis of spatial forecasting is discussed. Comparative study of the information method and regression analysis, the results are more consistent. According to the probability of failure value range (0,0.3), (0.3,0.5), (0.5,0?