Introduction: This work deals with the detection of adulteration of dairy products, which in some countries (especially the developing countries) is seen as a serious issue. Possible adulterants for milk fat (MF) are waste oils from both vegetal (sunflower, soybean, rapeseed) and animal (lard, beef/sheep tallow, chicken fat) origin. MF contrasts with other fats and oils by its short (C4-C6) and medium (C8-C12) chain fatty acids composition. The standard method to accurately determine of the fatty acids profile (FAP) of milk and dairy products is gas-chromatography (GC), which requires the methylation of the fatty acids to the corresponding methyl esters, prior to their chromatographic separation. As a result, the GC method is laborious and time-consuming, given the chromatographic separation step is also long (approximately 1 hour). Consequently, faster alternative methods are welcome. [1] Materials and methods: Three descriptors of conformity/adulteration were determined for each sample, based on the 1H-NMR data (in particular, based on the integral values of resonances associated with chain length, unsaturation, and butyric moiety). Each fat sample was consequently characterized by three numerical values, corresponding to the descriptors. Results: Cartesian 3D representation of samples revealed their clustering according to fat type, leading to good classification. Adulterated samples placed outside the groups, as outliers. Conclusions: The classification model according to the 1H-NMR based descriptors allows visualization of adulterated samples.