New kinetics families have been implemented in RMG to allow automatic enumeration of new reaction pathways. All of the new families which have been added since RMG v1.0.0 are shown in Table . A complete list of all families can be found on GitHub. These new kinetics families include reactions involved in the propargyl recombination pathway to benzene formation, peroxide reactions relevant in liquid phase oxidation chemistry, surface reaction types for heterogeneous catalysis simulations, and a few other reactions types which have been found to be important for various systems. The solution which is being introduced in RMG v3.0 is the capability of automatically generating the tree. The new method uses machine learning approaches to automatically generate a decision tree based on the available training reactions. Starting with a generic reaction template, new groups are generated based on pre-defined types of extensions, e.g., adding an atom, adding a bond, specifying an element, etc. An optimal extension is chosen at each level of the tree by determining information gain based on the reduction in reaction rate variance. More details of the algorithm will be described in a separate publication.