In this work, blends of olive and soybean oils were analyzed by near-infrared spectroscopy (NIR), mid-infrared (MIR), and Raman techniques to evaluate adulterations in olive oils. A representative group of different commercial brands of soybean oil and extra-virgin olive oil were analyzed by gas chromatography with flame ionization detector in order to explore the chemical similarity and composition of the fatty acid (FA) profile. Two stock solutions were prepared, one produced from a mixture of soybean oils and the other from the mixture of olive oils. From these stock solutions, 60 samples were prepared, simulating adulteration levels of extra-virgin olive oil with soybean oil between 0 and 100 %. It was possible to fit a model able to predict fraud within the interval investigated by partial least squares regression approach, with precision and accuracy values for root mean squared error of prediction of 1.76 (NIR), 4.89 (MIR), and 1.57 (Raman) and coefficient of determination R ² greater than 0.98 for the three techniques. The methodologies demonstrated to be very useful for the quantification of extra-virgin olive oil adulteration with soybean oil, presenting short analysis time, low cost, and absence of sample preparation procedures as main advantages.