To address the limita�ons of experimental and computa�onally demanding methods, predic�ve methodologies such as group contribu�on (GC) methods and machine learning (ML) algorithms offer efficient alterna�ves. Albahri introduced a more accurate GC method for compu�ng net heat of combus�on (NHOC). This method computes 32 atom-type structural groups for NHOC in up to 452 hydrocarbons, yielding NHOC predic�ons with an average absolute error of 0.71% and a correla�on coefficient (R) of 0.9982 . However, this method may be �me-consuming for many hydrocarbons and may be unsuitable for newly synthesized complex molecules. GC methods are empirical ,