Following the first iteration of the deconvolution procedure, compounds 2b, 2e, and 2f were removed because their predicted concentrations were all below the 5% concentration cutoff. A final iteration of the deconvolution procedure was performed with the remaining compounds 2a, 2c, and 2d to improve the resulting fit. As shown in Fig. , the procedure, once again, predicted the presence or absence of candidate compounds with 100% accuracy and predicted the concentrations of each compound present with an MAE of 1%, demonstrating the ability of our method to determine which components are present in the spectrum of a crude reaction and the relative concentrations of the components. The deconvoluted spectra are shown in Fig. . We next considered a significantly more difficult example: the borylation of 2-phenylethylpyridine (3a, Fig. ). The number of potential products from this reaction is larger, and many of the resonances of the protons in these products overlap. In addition, the experimental spectrum contains unassigned, low-intensity signals that correspond to impurities present in the reactant. The borylation can occur at any aromatic C-H bond of 2-phenyethylpyridine. Borylation of secondary benzylic C-H bonds is unlikely, so products from reaction at those positions were not considered. In total, the candidate library consisted of the 8 compounds shown in Fig. . To compensate for the impurity peaks, a cutoff of 10% was used during HMCMC fitting. NMR parameters for all candidate compounds were calculated and calibrated as described above to yield a set of predicted NMR spectra (Fig. ). Because the starting material was available, the NMR spectrum of the starting material was acquired, and the chemical shifts and splitting patterns of the peaks in the experimental spectrum were fit using MRsimulator, as described above, to obtain a better initial trial spectrum.