The reaction forward prediction models demonstrated their robustness not only by accurately predicting reaction outcomes for known substrates, as seen with the random split (i.e., 0D), which achieved a mean absolute error (MAE) of 6.7%, high correlation (r = 0.83) and a precision value of 90.9%, but also by successfully extrapolating to novel chemical space. When applied to unseen carboxylic acids and N -arenes independently (1D split) and combined (2D split), the models maintained robust performance, with MAEs in the range of 11.4-12.6%, precision values up to 85.4%, and correlation coefficients ranging from r = 0.51 to r = 0.55.