Comparing with safety factor method, reliability-based design method can quantify the uncertainty to design geotechnical structure in a more systematical and economical design. In this study, a multivariate probability distribution model for nine parameters of intact rock is constructed based on the ROCK/9/4069 database. These nine parameters are:(1)unit weight (γ);(2)porosity (n);(3)L-type Schmidt hammer hardness (RL);(4)Shore scleroscope hardness (Sh);(5)Brazilian tensile strength (σbt);(6)point load strength index (Is50);(7)uniaxial compressive strength (σc);(8)Young’s modulus (E);(9)compressional wave velocity (VP). Consistency is shown that the multivariate probability distribution can capture the correlation among the nine parameters. Using the Bayesian analysis framework, the original distributions of the design rock parameters (σc, E) would serve as prior distributions and can be updated into posterior distributions by using different multivariate site-specific information. The forms of posterior distributions were summarized into tables so that detailed Bayesian analysis need not be conducted. From the results, the transformation uncertainty of predicted posterior distribution can be effectively reduced as the multivariate site-specific information increases. With smaller uncertainty, reliability-based design can reduce more economical design.