As in the previous iteration of MLR modeling, we evaluated a multitude of steric and electronic parameters in this second model (see SI for more details). Those parameters that were included in the final model are depicted in Figure & 8C and include the same alcohol classifier and DEFMO terms used in the previous model, as well as two new steric terms, Bmax 2Å and Bmax 8.5Å. The latter two parameters are advanced sterimol descriptors recently introduced by Paton and coworkers. The parameters were measured by first defining an axis along the pyridine C4-C1' bond (depicted with a grey line, Figure ). The maximum and minimum steric measurements perpendicular to this axis (Bmax and Bmin, respectively) were collected at 0.5 Å intervals along the axis. The Bmax measurements collected at 2.0 Å and 8.5 Å led to the best MLR model. In order to further validate the robustness of the statistical model, we synthesized and tested an additional validation set of 4-biaryl aldehydes 10q -10t that were not used for statistical modeling (Figure ). These were synthesized from boronic acids that were already on hand in our laboratory via a Suzuki cross-coupling reaction. The aldehydes were then tested with alcohols 11a and 11b and the CD spectra of the resultant assemblies were measured. The original model was then retrained using all assemblies 12a -12p. We were pleased to find that assemblies 12q -12t were well predicted by the model (validation R 2 = 0.81). It should be noted that the compounds in the validation set featured both electron-poor (12t), electron-rich (12s), and p-extended (12q) arenes and a common 3,5-disubstitution pattern that was absent from the aldehydes used for model generation. This highlights the ability of the model to effectively predict the performance of unique, out-of-sample substrates.