Abstract: Rockburst prediction is of great significance to ensure construction safety. However, the spatial variability of rock mass parameters will lead to uncertainty in rockburst prediction results. In this study, rockburst tendency and its probability were studied in order to explore a more suitable evaluation method for rockburst tendency in engineering practice. Firstly, an improved cohesion weakening-friction strengthening model considering the dynamic change of rock dilatancy strength was established, and the rockburst tendency analysis was realized combined with energy index. On this basis, relying on the Dahongshan copper mine project buried with a depth of more than 1,000 meters, the point estimation-finite element analysis method was applied to the rock burst tendency analysis. A finite element model with initial cohesion, residual cohesion, residual friction angle, viscous plastic strain critical value, critical value of cohesion plastic strain and critical value of friction angle plastic strain as input variables, and rockburst depth, range, and local energy release value as output variables was constructed, and the specific methods and steps of problem analysis were clarified. Furthermore, the probability model of rockburst failure is obtained, and the probability distribution of rockburst area was obtained by meshing the failure elements and the weight combi-nation of different scheme results. The research results show that: Compared with other methods, the used con-stitutive model and indexes can represent the rockburst failure better; After considering the variability of rock mass parameters, the depth of rockburst was in good agreement with the depth recorded in the field, which verified the feasibility and correctness of the uncertainty analysis. In addition, the unspecified range and local energy release value in the data were predicted; The optimal distribution of rockburst depth, range and local energy release value was Normal distribution Gamma distribution and Lognormal distribution, respectively. The probability distribution map of the rockburst area could judge the area and probability of rockburst damage more intuitively and reasonably. The research results have reference significance for rockburst support and risk assessment.