The common chemometric qualitative and classification non-supervised approaches include principal component analysis (PCA), cluster analysis (CA), or soft independent modeling of class analogy (SIMCA), while the supervised methods include partial least squares (PLS) with discriminant Analysis (PLSDA), linear discriminating analysis (LDA) and principal component regression (PCR) [19; 20; 21]. The chemometric algorithm used in PCA and PLS has been extensively used to obtain different quality parameters of edible oils [16; 22; 23] and applied to the evaluation of fatty acids composition and other quality parameters of virgin olive oil [4; 24]. The Random forest algorithm has been applied as a one-class classifier in FTIR spectroscopy for food adulteration and showed superior performance comparing to PLS-DA and SIMCA, for classification and authentication in chemometrics [25]. The web-based software MetaboAnalyst 4.0 ([[https://www.metaboanalyst.ca/](https://www.metaboanalyst.ca/)]([https://www.metaboanalyst.ca/](https://www.metaboanalyst.ca/))) is a complex processing tool which accepts a variety of input data (from NMR and MS to FTIR peak lists) and offers a number of chemometric options for data processing, from univariate (ANOVA \(t\)-test) to multivariate statistical analysis, PCA, PLS-DA, CA, heatmaps, Random forest and a number of more sophisticated statistical or machine learning methods [26]. Different reviews [5; 27] and experimental data have been reported, about the FTIR spectroscopy applied for the characterization of edible (especially olive) oil quality [10; 26; 28; 29], as well as for the freshness evaluation [24] and detection of adulteration [4; 12; 30; 31; 32]. A large majority of data refer to olive oil adulteration with low cost edible oils [28; 33; 34] or to assess oil oxidation [6; 34; 35]. Fewer references are related to specialty, functional oils which have beneficial impacts on health and cardiovascular or other disease prevention. To mention, some articles reported the FTIR fingerprint of walnut, linseed and soybean oils, pumpkin [36; 37; 38; 39], hempseed oils [40] or sea buckthorn oils [41]. The grapeseed, nigella seed neem oils, as well as wheat germ, sesame oils or flaxseed, coconut and rosehip oils which exhibit pleasant flavor and health benefits are often counterfeited and adulterated with other low-cost oils, drawing wide attention [36; 38; 42; 43; 44; 45; 46]. The evaluation of different liquid foods (beverages, fruit juices) as well as edible oils, using ATR-FTIR fingerprinting, represented our previous interests and former investigations using complementary techniques, such as UV-Vis spectrometry, ATR-FTIR-MIR spectrometry, liquid chromatography coupled with diode-array or mass spectrometry (MS) detection MS detection, or gas-chromatography coupled with MS [2; 47; 48; 49; 50; 41]. We report here the evaluation of seven types of cold-pressed functional oils produced in Romania, provided directly from small enterprise manufacturers (as genuine, process-controlled authentic samples) and comparatively from similar oil types (including also olive oils), as commercial samples labeled as \"cold-pressed\" or extra-virgin. We applied UV-Vis spectrometry and ATR-FTIR-MIR spectroscopy, to identify the specific fingerprints of oils from different botanical origins and related to their quality, compared to commercial oils of the same botanical origin, possibly mislabeled or adulterated. The FTIR data were analyzed by chemometrics successively using Unscrambler X.10.4 and Metaboanalyst 4.0 software. Finally, we were able to consider the most relevant biomarkers, to classify and discriminate the eight oil types based on their botanical origin, authenticity, and quality.