Food fraud has been common in recent decades. Motivated by the illicitly acquired profit, it can be the result of exchange between more expensive products for others of lower value. Oils have been target to adulteration since long time ago. Coconut oils, in the Market, can present prices are about 10-20 times higher than common plant oils like soybean. Authentication can be explained as a process of determining whether the study object is actually commensurate with the stated in its specifications. Non-destructive methods and chemometrics tools have been used to obtain rapid and relatively inexpensive analysis. Among the many chemometric tools, we can be emphasized authentication methods with class modeling, which can be applied to problems in which there is only a single class of interest. Among the most important authentication methods we can highlight DD-SIMCA (soft independent modeling of class analogy). Detection of falsification in foods is a typical example of authentication problems. In this work, Raman spectroscopy in conjunction to DD-SIMCA was applied for detection of several adulterants and authentication of coconut oils. The spectra were obtained using Raman Station 400F, from Perkin Elmer, laser of 785 nm, 30 seconds of exposition and 8 scans for each sample, range of 3200 -200 cm-1 with resolution of 2 cm-1.Ten vegetables oils and two mineral oils, had been used as adulterants in this work. The pure coconut oil was adulterated the range of 2-30% for each oil. Sixteen coconut oil reference samples were used for calibration and 100 adulterated samples were used for test. The model was able to classify the all pure coconut oils samples, as a target group, and differentiate from adulterated oils, with sensitivity and specificity of 100%. One class model strategy was a good approach for identify pure coconut oils from adulterated oils by Raman spectroscopy.