Adulteration of honey is a major problem in the food industry. The purpose of the present study was to classify different types of monofloral honey based on physicochemical characterization and analysis of phenolic compounds coupled with chemometrics methods. The methods for classification were trialed on a wide range of honey samples from different floral origins. For thyme, jujube, coriander, barberry, acacia and alfalfa honey samples, principal component analysis combined with discriminant analysis (PCA-DA) and partial least squares combined with discriminant analysis (PLS-DA) were trialed. The results indicate that the botanical origin of the honey affects the profile of flavonoids and phenolic compounds. For example, jujube honey samples had the highest amounts of hesperetin and chrysin, while thyme honey had the maximum amount of caffeic acid; the highest levels of quercetin and p-coumaric acid were found in coriander honey. To reduce the numbers of independent variables for modeling, the principal component analysis (PCA) algorithm was used. The three scores extracted from PCA had 83.17% variance. The classification results show that PLS-DA was successfully used to predict the class membership of honey samples (100%), but PCA-DA gave the lowest correct classification rate (97%).