To the best of our knowledge, this study represents the first application of Granger Causality analysis to a complex chemical reaction-specifically, the C-N coupling reaction step catalysed by [Cu(C8PhenMe6)I]and serves as a proof of principle. However, the model provides a simple interpretation of causality, as it analyses pairs of variables and not more complex composite variables. Transitioning to more advanced causal discovery methods, such as PC Momentary Conditional Independence (PCMCI)-based approaches, would enable better interpretation of nonlinearity and the presence of hidden variables within the dataset. Nonetheless, such advancements are beyond the scope of this work. To quantify the changes in internal coordinates, we employed a Decision Tree trained on the three ensembles, which highlighted the Cu-C and C-N distances as being the main feature for separating products from educts and transition states, respectively. However, Decision Trees are dependent on the initialisation condition and must be limited in their size to maintain interpretability. A transition to the Decision Rule approach overcomes some of the limitations by assigning a semantic interpretation to a RF classifier, thus, clearly separating the three ensembles. In addition, three distinct product conformers are identified, each defined by a unique set of decision rules and distinguishable in the PCA consensus features plot (Figure ). Structural differences can be inferred from analysis of IC2 of the tICA analysis and PC2 of the PCA, indicating, as expected, changes in cage conformations. These conformations will likely converge as the product diffuses out of the cavity.