Asian Journal of Mathematics and Computer Research

The Zagreb vector indices were introduced as an extension to capture more structural information simultaneously. Unlike traditional scalar indices, Zagreb vector indices provide a multidimensional representation of molecular topology that considers interrelated parameters in a unified framework, thereby improving the accuracy of molecular discrimination and prediction. In this paper, we investigate the variation in the physical properties of a series of aliphatic hydrocarbons using the Zagreb vector index and the VL-index. Multiple linear regression models are employed to predict key physicochemical properties, specifically melting and boiling points. The results demonstrate the effectiveness of these vector- and VL-based topological indices as reliable descriptors in regression modelling using R. Optimal regression curves remain challenging due to multifaceted molecular influences, hydrogenation and polymerization processes revealed linear property trends, addressing key chemical, mathematical, and statistical challenges in quantitative structure-property relationships.