This paper presents a probabilistic analysis framework for the reliability evaluation of turbine disc considering the correlation of multi-failure modes. A system-level zone division method is first applied to decompose the whole structure into different serial zones. Due to the same input random variables, there is correlation between failure modes. Thus, a mathematical copula function method is introduced to quantify the correlation between failure modes after reliability calculation of separate zones, during which process, dependent random variables are transformed to independent ones using Nataf transformation method. Meanwhile, to guarantee the accuracy and efficiency of calculation, adaptive surrogate model based on local radial point interpolation method (LRPIM) is established in each zone. Two main failure modes, i.e., low cycle fatigue and creep-fatigue are considered during the reliability analysis on a turbine disc. The results reveal that the reliability of the turbine disc changes with the correlation between failure modes. Also, sensitivity analysis shows that rotating speed and maximum temperature are two dominant factors affecting the turbined disc's reliability. Finally, the comparisons among three methods including the proposed method, the zone-based method without considering correlation and Monte Carlo (MC) method based on physics of failure (POF) of correlation are conducted. It is demonstrated that the proposed method in this study is more efficient and accurate for evaluating structural reliability with multi-failure modes coupling. Moreover, the proposed method provides an available prospect for reliability-based design optimization of multiple failure structure, contributing to enhance reliability in mechanical design.