Statistical analysis and clustering of discontinuities existing in rock mass are the basis of rock mass engineering stability analysis. Considering that the mechanical and hydraulic properties of discontinuities are affected by many factors such as occurrence, trace length, opening, roughness, and filling state. A multi-parameter dominant grouping method of rock mass discontinuities based on principal component analysis is proposed. Firstly, the principal component analysis method is used to select the criterion of the dominant grouping and calculate the weight value of its participation in similarity measurement. Secondly, the global optimal initial clustering center of the fuzzy C-means clustering algorithm is searched using the annealing genetic algorithm. Lastly, the objective function is established by minimizing the weighted sum of the distance between the discontinuities to be grouped and the clustering center, achieving the dominant grouping of multi-parameter rock mass discontinuity. The 200 discontinuities simulated by the computer are divided into dominant groups using the multi-parameter method and compared with other methods. The results show that this method has higher grouping accuracy. The method is applied to the multi-parameter dominant grouping of the measured discontinuities of Huayang Tunnel of Chongqing Third Ring Expressway. The grouping results are reasonable and reliable, which further verify that the method has significant engineering application value.