A rock mass classification system is intended to classify and characterize the rock masses, provide a basis for estimating deformation and strength properties, supply quantitative data for mine support estimation, and present a platform for communication between exploration, design and construction groups. In most widely used rock mass classification systems, such as RMR and Q systems, up to six parameters are employed to classify the rock mass. Visualization of rock mass classification systems in multi-dimensional spaces is explored to assist engineers in identifying major controlling parameters in these rock mass classification systems. Different visualization methods are used to visualize the most widely used rock mass classification systems. The study reveals that all major rock mass classification systems tackle essentially two dominant factors in their scheme, i.e., block size and joint surface condition. Other sub-parameters, such as joint set number, joint space, joint surface roughness, alteration, etc., control these two dominant factors. A series two-dimensional, three-dimensional, and multi-dimensional visualizations are created for RMR, Q, Rock Mass index RMi and Geological Strength Index (GSI) systems using different techniques. In this manner, valuable insight into these rock mass classification systems is gained.