Chemical graph theory is an important field in mathematical chemistry that uses domination degree‐based indices to convert the chemical structure of molecules into numerical values. These indices help investigate physico‐chemical properties, pharmacokinetic properties, and biological activity in QSPR and QSAR studies. Among the most life‐threatening diseases, cancer remains a major global health concern. Various anticancer drugs like Tegafur, Floxuridine, etc., are employed to combat different cancer types. This paper designs a QSPR model to predict selected physico‐chemical and ADMET properties of these anticancer drugs using indices like the first, second, and modified first Zagreb domination topological index; forgotten, hyper, and modified forgotten domination topological index; and first, second, and modified first Zagreb ‐domination topological index; forgotten, hyper, and modified forgotten ‐domination topological index, via ‐ and ‐polynomials. The relationship analyzes for these properties with the domination degree‐based indices are conducted using the inverse cubic regression method. The results can correlate with other properties, aiding in constructing a disease‐based drug library.