The MCS-based method succeeds in 81% (Golden dataset) to 100% (Urnd of the test cases, see Fig. and Supplementary Table . Fig. depicts some reactions that were successfully balanced by the MCS-based method. It showcases the application of a list of different expand and merge rules. In contrast to the rule-based approach, the prediction accuracy on successful cases is not fully satisfactory on all test sets. While the predictions are close to perfect on the USPTO-based datasets, and about 95% for the Jaworski's data, only about 80% are achieved on the Golden set. The differences in success rates between the datasets can be attributed primarily to differences in the frequency of reactions that cannot be balanced by the MCS-based approach, in particular rearrangement reactions, ring-formations, or complex reactions with many compounds.