As with the progress of human knowledge, the use of underground space is increasing. To design and construction of underground excavations, it is important to know the rock mass properties. The determination of the rock mass properties is one of the most difficult tasks that has always been had a great importance in the field of rock mechanics. In rock engineering practice due to of the cost of the required tests, the required data are often inadequate and therefore are always consist of uncertainties. Some uncertainties in the input parameters for the design of underground excavations, such as rock mass strength parameters and deformation modulus, are inherent and others due to lack of knowledge or understanding of these parameters. To quantify the effects of these uncertainties on underground excavations design, it is necessary to utilize probabilistic analysis methods. In this study, a statistical method to determine the geological strength index (GSI) is used. It employs the block volume and joint condition factor as quantitative characterization factors to determine the GSI values. This method is based on the relationship between descriptive geological terms and measurable field parameters such as joint spacing and joint roughness, which are random variables. Using GSI distribution was obtained from field mapping data and combination with the intact rock strength properties, which are also statistical, the probability distributions Functions of rock mass strength parameters (Hoek Brown strength parameters mb and s, or the equivalent Mohr–Coulomb strength parameters c and ?) and deformation modulus of the rock mass was calculated by using Monte Carlo method in Excel add-in @RISK. This method was applied to determination mechanical properties the jointed rock masses at the Azad Pumped Storage Powerhouse. Then, based on variable input parameters, statistical analysis of stability of Azad Pumped Storage Powerhouse cavern was accomplished. After that, rock load and deep of plastic zone around the cavern were determined. Finally, according to these parameters suitable support system has been offered. The method presents an approach for systematic assessment of uncertainty in rock mass characterization in rock engineering, and it can assist us to better understand how uncertainty arises and how the rock support system design decision may be affected by it.