The aim of this work was the foodinformatic (chemoinformatic) modeling of volatile organic compounds (VOCs) of different samples of peppers based on a quantitative structure-property relationship (QSPR) for the retention indices of 273 identified compounds. The experimental retention indices were measured by means of comprehensive two-dimensional gas chromatography combined with quadrupole-mass spectrometry (GC × GC/qMS) using the BPX5 and BP20 column coupled system. All the VOCs were represented by means of both conformation-independent molecular descriptors and molecular fingerprints calculated in the Dragon and PaDEL-Descriptor software. The dataset was divided into training, validation and test sets of molecules according to the Balanced Subsets Method (BSM). Subsequently, the V-WSP unsupervised variable reduction method was used to reduce the presence of multicollinearity, redundancy, and noise in the initial pool of 4,336 molecular descriptors and fingerprints. Using this method, a reduced pool of 1,664 was submitted to the supervised selection by means of the replacement method (RM) variable subset selection in order to define a four-descriptor model. The quality of the model was measured by means of the coefficient of determination and the root-mean-square deviation in fitting (R2 train = 0.879 and RMSDtrain = 72.1), validation (R2 val = 0.832 and RMSDval = 91.7), and prediction (R2 test = 0.915 and RMSDtest = 55.4). The negligible differences among the parameters in the three sets indicate a stable and predictive QSPR model. This quantitative structure-activity relationship was developed keeping in mind the five principles defined by the Organization for Economic Co-operation and Development (OECD) to make it applicable.