In this study, the Raman spectroscopy was used to detect honey adulterated with fructose (F), glucose (G), inverted sugar (IS), hydrolyzed inulin syrup (IN), and malt must (M). Thus, 56 samples of authentic honeys (acacia, sunflower, tilia, polyfloral, and honeydew) and 900 adulterated samples (with 5, 10, 20, 30, 40, and 50% fructose, glucose, inverted sugar, malt must, and hydrolyzed inulin syrup) were analyzed. The classification of honey authenticity has been made using the partial least square linear discriminant analysis (PLS-LDA), and a total accuracy of 96.54% (authentic honey vs. adulterated honey) was observed, while in the case of adulterated honey, a total accuracy of 90.00% was observed, respectively. The determination of the adulterant agent concentration has been made using partial least squares regression (PLSR) and principal component regression (PCR) methods. The proposed method can be considered easy and rapid for honey adulteration detection to provide continuous in-line information.