Ozone can react with fatty species such as vegetable oils to form oxidized compounds with interesting antibacterial activity. The iodine and peroxide indexes of these ozonated products are two crucial antibacterial characteristics. Currently, these two parameters are determined by chemical methods, which is disadvantageous because it requires long handling time, sample destruction and the use of toxic products. Spectroscopic analyses coupled with chemometric evaluations have already shown their usefulness for characterizing virgin oils via rapid, chemical-free methods. In addition, infrared spectroscopy is widely used to characterize ozonated compounds. The present study evaluates the possibility of coupling infrared spectroscopy with chemical analyses of ozonated compounds. We subjected 187 fat samples of varying compositions to different ozonation conditions to determine their chemical parameters. We analyzed the samples by infrared spectroscopy and modeled the results by combining chemical data with spectral analysis. The model results are quantified by the coefficient of determination R-2, the root-mean-square error, and the residual predictive deviation (RPD). The model produces RPDs greater than 3.5 for the mid-infrared spectral range, which means that they may be used to estimate indexes. In addition, with RPDs between 2 and 3, partial least squares near-infrared models demonstrate a capacity for rough screening of ozonated fats.