We evaluated the accuracy of the NEIMS (v. 1.0) machine learning spectral prediction algorithm for monosubstituted α-amino acids found both within, and beyond the algorithm's training set. We did so by measuring the accuracy of RMSE, SCA, and WCS. Our intent is to inform researchers who rely on predicted spectra for detection of unknown biomolecules, specifically amino acids. Results indicate that current machine learning algorithms are probably insufficient to predict spectra accurately.