The trained model is interpretable as the computed molecular features (depicted in Fig. center) associated with the decision tree nodes exhibit a connection to the stability of Cu-species within a possible catalytic cycle (28) (Fig. right). Notably, as recently reported by Hartwig et al., different mechanisms can be operative, changing as a function of structural features on the ligand, which also is likely influenced by the nature of the coupling partners . The initial node is reminiscent of the ligand re-selection step above; it splits the dataset according to the computed Cu-L interaction distance (d)-reactions employing ligands with computed d exceeding 2.07 Å are classified as off, yielding <20%. As previously discussed, the computed d can be interpreted as the stability of the Cu-L complex in the reaction medium, its capacity to enter the catalytic cycle, or potentially its ability to undergo oxidative addition. The subsequent node employs the computed nitrogen atom natural bonding orbital (NBO) charge of the primary amine substrate (N 𝛿 - ). Reactions involving primary amines with low nucleophilicity (N 𝛿 -> -0.803 au) are identified as unfavorable according to the trained model. This finding aligns with step ii in the catalytic cycle, indicating that the success of Ullmann couplings hinges on the primary amines capability to bind to the Cu center. The final node utilizes the computed buried volume (%VBur, 2.5 Å radius) of the aryl-bromide. Reactions with aryl-bromides exhibiting high steric hindrance (%VBur > 33.5%) are classified as producing yields below 20%. This molecular feature is a measure of the steric environment on the ipso-carbon and could potentially connect to several steps in the catalytic cycle, such as impeding the oxidative addition, amine binding, or the reductive elimination in step iii.