In the area of medical industry, the medical diagnosis classification problem has been given due attention for the sake of generating a vision-based structure and conceptualize some 3D models for an automated monitoring. The present paper comprehensively addresses the probabilistic randomness with the help of T-spherical fuzzy sets and focus on introducing a probabilistic information distance measure for the T-spherical fuzzy environment. The introduction of measure incorporates probability of occurrence & non-occurrence of T-spherical fuzzy information in an integrated way and explained with an illustrative example and validation with some results. Further, an algorithm utilizing the proposed information measure for the T-spherical fuzzy set up has been presented for handling a kind of building material classification problem based on the observations and professional judgment. The purpose of the presented methodology is to have the identification of unknown material in the construction management. Based on an empirical hypothetical data, a numerical example which is in connection with classification of building materials has been solved to demonstrate the presented methodology.