The ALFABET model is more competitive in giving accurate BDEs for species containing C,H,O, and H. However, the BEBOP model has strengths in generating QC-based bond energies essential for general chemistry applications. ML models can generate large numbers of optimizable parameters to extrapolate the energy from thousands of data. The BEBOP implementation is far more robust than ML models for the following reasons: (i) equations are physically rooted on the SQM formalism, (ii) the current parameters are physically-based and transferable across chemical space, (iii) the number of parameters is small, (iv) 36 reference species were used for parametrization, and (v) the model attempts to extrapolate the ROCBS-QB3 total electronic energy well for hydrocarbons (especially C -H bond in alcohol).