In the current era of technological advancement, dendrimers have been in high demand as the fundamental component in the field of drug design. For better efficacy, scientists have been working intensely to produce potentially beneficial dendrimer molecules. Mathematical chemistry has a lot to offer with effective tools like molecular descriptors and functions that can forecast compound molecular features. Topological descriptors, being numerical invariants associated with a chemical compound, have the potential to correlate chemical structure with different physical attributes, chemical reactivity, or biological activity. By incorporating these descriptors in QSAR and QSPR modeling, it is possible to predict a variety of physicochemical attributes and bioactivities. Hence, the main objective of the study is to obtain the distance‐based molecular descriptors of triazine‐based dendrimer and subsequently generate linear models for their chemical properties using regression analysis. This linear model can predict the properties of succeeding generations, avoiding the necessity for time‐consuming laboratory experimental trials.