The compilation and utilization of an in silico IR spectral library of ionized molecules for the identification of unknown metabolites using MS-based IRIS experiments has been demonstrated. An automated workflow to produce IR spectra of molecular ions generated over 75000 DFT-calculated vibrational spectra for 4640 metabolites taken from the HMDB. A scoring algorithm based on cosine similarity was employed to identify the molecular structures that match favorably with a user supplied experimental IR ion spectrum. By collecting a set of 189 experimental IRIS spectra we evaluated the performance of the in silico IR spectral library in the identification of metabolites. With a known accurate mass value and working within the boundaries of our data set, 75% of metabolites was correctly identified, which further improves to 83% by simultaneous identification of multiple ionic adducts of the same metabolite.