In summary, the dataset utilized for model training and testing consisted of atomic numbers, charges, electronegativities, mass numbers, and label-encoded symbols of each fluorine atom's neighbors as input features (X). The compounds' corresponding DFT shifts were considered as the output (y). While DFT can shorten the time needed to calculate the shifts of all 501 compounds-in contrast to producing experimental 19 F NMR shifts over the course of months or years (depending on dataset length)-DFT has limited predictive power. Imperatively, computational methods will never be equal in accuracy to real experimental methods .