Using a modular amino acid based chiral ligand motif, a library of ligands was synthesized systematically varying the substituents at two positions. The effects of these changes on ligand structure were probed in the enantioselective allylation of benzaldehyde, acetophenone, and methylethyl ketone under Nozaki-HiyamaKishi conditions. The resulting three-dimensional datasets allowed for the construction of mathematical surface models which describe the interplay of substituent effects on enantioselectivity for a given reaction. The surface models were both extrapolated and manipulated to predict the enantioselective outcomes of several previously untested ligands. Analyses were also used to predict optimal ligand structure of a minimal dataset. Within the dataset, a linear free energy relationship was also discovered and a direct comparison of both the linear prediction as well as the threedimensional prediction illustrates the potential predictive power of using a three-dimensional model approach to asymmetric catalyst development.A centerpiece of modern organic chemistry is the development of new catalytic enantioselective methods to obtain valuable enantiomerically enriched synthetic building blocks (1, 2). Asymmetric catalysis, in practice, initiates from the discovery of a new catalytic reaction or identification of a reaction of interest. Subsequently, a number of chiral ligand classes are experimentally explored in hope of finding a "lead" which generates a promising enantiomeric ratio (er). Further optimization of the reaction conditions and ligand structure can ultimately yield a mature catalytic asymmetric method. This process is highly empirical and the results can be unsatisfactory for a given reaction. The empiricism inherent in reaction development has been addressed by computational chemistry via stereocartography and various other methods (3-10). Even with the impressive impact computational chemistry has had on the field, the small energy differences in the diastereomeric transition states (∼2-3 kcal∕mol or 8.2-12.3 kJ∕ mol) leading to enantiomerically enriched products are not easily rationalized. Additionally, these methods generally depend on a detailed understanding of the parent chiral catalyst structure. Furthermore, kinetic analyses of asymmetric catalytic reactions often reveal the general complexities of catalysis and highlight the importance of the Curtin-Hammett principle (11, 12), but do not often expose the key catalyst structural features responsible for enantioselection. These issues highlight an underlying challenge in the field of asymmetric catalysis: how does one design a ligand for a given reaction type without engaging in a longterm, empirical investigation of multiple ligand classes?A goal of our program has been to utilize classic linear free energy relationships (LFER) to predict the enantioselective outcomes of new catalytic systems (13). We have recently disclosed the use of steric parameters originally developed by Taft and modified by Charton (14-17) to quantitatively ...