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Background: Quantitative Structure-Activity Relationship (QSAR) studies describing the correlations between biological activity as dependent parameters and physicochemical and structural descriptors, including topological indices (TIs) as independent parameters, play an important role in drug discovery research. The emergence of graph theory in exploring the structural attributes of the chemical space has led to the evolution of various TIs, which have made their way into drug discovery. The TIs are easy to compute compared to the empirical parameters, but they lack physiochemical interpretation, which is essential in understanding the mechanism of action. Objective: Hence, efforts have been made to review the work on the advances in topological indices, their physicochemical significance, and their role in developing QSAR models. Methods: A literature search has been carried out, and the research article providing evidence of the physicochemical significance of the topological parameters as well as some recent studies utilizing these parameters in the development of QSAR models, have been evaluated. Result: In this review, the physicochemical significance of TIs have been described through their correlations between empirical parameters in terms of explainable physicochemical properties, along with their application in the development of predictive QSAR models. Conclusion: Most of these findings suggest a common trend of TIs correlation with MR rather than logP or other parameters; nevertheless, the developed models may be useful in both drug and vaccine development