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Predicting the penetration rate plays a key role in tunnel projects using a tunnel-boring machine (TBM). Developing accurate prediction models can improve project management, save budget, and time in tunnel projects. In this research, the Gelas water project data was used to obtain new statistical models for predicting TBM penetration rate per revolution (PRev) utilizing the toughness index (Ti), modulus ratio (E/UCS), and joint parameters (JP). The relationship between various geomechanical properties and rock classification systems, including uniaxial compressive strength, Brazilian tensile strength, Young's modulus, joint parameter, toughness index, rock quality designation, rock mass rating, geological strength index, rock mass quality, and rock mass index analyzed and considered on TBM performance in sedimentary, igneous, and metamorphic rocks. The statistical analysis clearly shows that Ti revealed a significant correlation with actual PRev (R2=0.75). Additionally, the PRev was computed using Ti, and JP showed good agreement with the coefficient of determination (R2), i.e., 0.79. Results indicated that the Ti decreased by increasing the modulus ratio, so the PRev increased. This model can be used easily since it provides a straightforward predictive model using the multi-parameter model.