Encouraged by the results from the O-pyranoside glycosylation model validation study, we set out to develop models that could accommodate an even larger chemical space by including S-and N-glycosylation, as well as furanosides. Moreover, we wanted to extend the objective of the model to not only include the predictions of the major product but also the prediction of the ratio of products in a more quantitative sense. Predicting anomeric ratios is a non-trivial task, and such a model would be a valuable tool in the field of carbohydrate chemistry. Due to a skewed distribution of glycosylation yielding a single product and a mixture of anomers as products in both the CAS dataset, 8588 vs 1846 respectively, and the Barresi-Hindsgaul dataset, 536 vs 141 respectively, we also developed a classification model to predict whether a minor product is likely observed alongside the major anomer. The three types of predictions are integrated into the "GlycoPredictor" as illustrated in Figure . From the input (reaction SMILES and reaction conditions), the major anomer is predicted, before predicting if the minor anomer is likely to be observed. If so, the quantitative anomeric ratio is predicted, otherwise it is set to 100% of the major anomer and the predicted Mills configuration ratio is translated into the α:β ratio.