Mentha arvensis essential oil is considered a product of high economic value that finds application in the food, pharmaceutical, and cosmetic industries. They are subjected to adulteration with synthetic chemicals and low-cost vegetable oils with higher boiling points. A rapid, non-destructive method using infrared spectroscopy has been investigated to authenticate Mentha arvensis Essential oils, helping to maintain their quality and trustworthiness for users who rely on them for their beneficial properties. Authentic samples of Mentha arvensis essential oil were obtained and analyzed using Attenuated Total Reflectance-Fourier Transform Infrared spectroscopy in the wavenumber range of 500–4000 cm−1. The resulting spectra were pre-processed with Multiplicative Scatter Correction. The initial investigation involved exploratory analysis using Principal Component Analysis, followed by discriminant analysis using Principal Component Analysis-Linear Discriminant Analysis, Partial Least Squares-Discriminant Analysis, and Soft Independent Modelling for Class Analogy. The classification models developed have a high accuracy of 100 % thus demonstrating higher efficiency in distinguishing different adulterants in Mentha arvensis essential oil with both high specificity and sensitivity. To assess the extent of adulteration in Mentha arvensis essential oil, Partial Least Squares Regression and Principal Component Regression were employed. The regression models were capable of identifying adulteration levels as low as 5 % in the essential oil thus enabling FTIR spectroscopy coupled with chemometrics to serve as a non-destructive method for identifying commonly used adulterants, potentially replacing traditionally used Chromatographic and Thermo-Gravimetric Analysis methods.