To evaluate the performance of the HMCMC fitting portion of the workflow, we conducted a series of benchmark tests. These benchmarks are designed to evaluate the ability of the HMCMC procedure to analyze NMR spectra of reaction mixtures and autonomously identify the constituents. The value of our method is that it is tolerant of errors in the chemical shifts of the resonances in a spectrum of a crude reaction mixture, allowing us to use calculated spectra in place of those derived from experimental data. To test the impact of errors in the predicted chemical shifts of the reaction components, we considered three levels of NMR predictions with varying accuracy. The first, a rule-based NMR prediction implemented in ChemDraw ® , is characterized by a standard deviation of roughly 0.4 ppm in the predicted chemical shifts. The standard deviation of chemical shifts calculated by DFT using the functional and basis set described above was found to be roughly 0.1 ppm. Finally, these approaches to chemical shift estimation are compared against the use of known spectra from a chemical library repository, which represents the best-case scenario of having known NMR spectra. Because our method requires a standard deviation parameter, we assign a chemical shift standard deviation of 0.01 ppm for molecules with a known spectrum. These three methods (ChemDraw ® , DFT, and library sources of NMR spectra) were compared in three benchmark tests: 1) fitting a complex spectrum containing n number of compounds using a candidate list of n molecular structures (in which n = 5 or 10); 2) the same procedure as (1) with the addition of random noise to the baseline of the true spectrum; and 3) fitting a complex spectrum containing 5 compounds using a candidate list of 10 molecular structures, with and without the addition of baseline noise.