A quantum cascade laser spectrometer was used to obtain the reflection spectra of highly energetic materials (HEMs) deposited on nonideal, low-reflectivity substrates, such as travel-bag fabric (polyester), cardboard, and wood. Various deposition methods were used to prepare the standards and samples in the study. The HEMs used were the nitroaromatic explosive 2,4,6-trinitrotoluene (TNT), the aliphatic nitrate ester pentaerythritol tetranitrate (PETN), and the aliphatic nitramine 1,3,5-trinitroperhydro-1,3,5-triazine (RDX). Chemometrics algorithms were applied to analyze the recorded spectra. Partial least squares (PLS) regression analysis was used to find the best correlation between the infrared signals and the surface concentrations of the samples, and PLS combined with discriminant analysis (PLS-DA) was used to discriminate, classify, and identity similarities in the spectral datasets. Several preprocessing steps were applied to prepare the mid-infrared spectra of HEMs deposited on the target substrates. The results demonstrate that the infrared vibrational method described in this study is well suited for the rapid screening analysis of HEMs on low-reflectivity substrates when a supervised model has been previously constructed or when a reference spectrum of the clean substrate can be acquired to be subtracted from the HEM-substrate spectrum.