For both the two expert trees and the decision tree algorithm, the root node focuses on the C-2 substituent. Expert 1 starts by asking if the C-2 substituent is an ester, i.e., if NGP is possible, and thereafter questions the orientation of the C-2 substituent, whereas Expert 2 starts by asking if the glycosyl donor has a substituent on C-2, i.e., if it is a 2-deoxy glycosyl donor, followed by questioning the orientation and then the possibility for NGP. Interestingly, Expert 2's assumption that most glycosylations with 2-deoxy glycosyl donors yield the α-anomer as the major product seems to be wrong as the dataset suggests that a slight majority of 2deoxy glycosylations are β-selective. However, controlling the stereochemical outcome of 2-deoxy glycosylation is a known challenge within carbohydrate chemistry. Both experts then ask whether the solvent used is acetonitrile. The results indicate that assuming β-selectivity for glycosylations in acetonitrile is reasonable, provided the glycosyl donor has an equatorial substituent and lacks neighboring group participation (NGP). However, a lot of accuracy is lost for both expert trees by assuming α-selectivity if the solvent is not acetonitrile, thus our understanding of the factors governing the stereochemical outcome for these types of glycosylations has room for improvement. In addition, Expert 2 adds a decision node for 2,6-benzylidene-protected mannosides which is a known method for obtaining β-selective mannosylations , and this selectivity is also substantiated by the dataset. Overall, the expert decision trees are notably similar in both performance and what factors are considered at each decision node, though Expert 2's tree takes a more linear approach whereas Expert 1's tree is more branched.