In this work, principal component analysis (PCA) and Partial Least Square Regression (PLS) are applied to the FT-IR spectra of beers differing in flavor, type, alcohol content and producer, to identify the spectral parameters that may provide rapid information about factors affecting beer quality. In total 32 different beers were collected at the local Interspar hypermarket in the mall Malompark, Füredi street 27, 4032 Debrecen. Due to the samples 6, 17 and 28 were not available at the second sampling in the local market, their analytical and spectra data were excluded from this work. The final beers were 20 lager and 9 ale samples, which 22 were nonflavored,and 7 were flavored with sour cherry, raspberry, blueberry, mango, orange and ginger.According to the labels, the range of alcohol content was between 4,0 to 5,5 (%V/V). Prior to the analysis, the samples were identified, decarbonated and filtered. The total acidity, color intensity, alcohol content, bitter acid content, dry matter and elemental content were quantified by classical and instrumental procedures, as titration, spectrometry and ICPOES.The FT-IR spectra were collected in triplicate of each sample, with the air as background. The PLS and PCA were performed with the assistance of the software The Unscrambler X. The entire spectra were selected for PCA and PLS analysis, including the region between 650 to 4000 cm-1. For both methods the spectra matrix was transformed by the derivative Savitzky-Golay method before the running of the multivariate analysis. In PLS modelling the derivatized spectra was used as X-variable data set, and the analytical data and elemental content were analyzed as Y-variable (alcohol content, bitter acid content, total acidity, flavor,type of fermentation, producer, color intensity, Na, Ca, K, P, Mg, and S content). The first two principal components of the PCA, explained majority of the variance in the data set. In addition, the application of ranges calculated from the analytical and elemental content results could explain the scattering and groups displayed on the PCA space based on type of fermentation, total acidity, flavor and non-flavor characteristics. The PLS predictions for flavored beers demonstrated strong correlation between the tradionally measured values (bitter acid content, total acidity, color intensity and dry matter), phosphorus and potassium content and the spectra. The PLS predictions for all flavored beers and non-flavored beers presented good covariation values for the total acidity and alcohol content, respectively. The confirmed that the combination of FT-IR with chemometric tools can provide corelations between the spectra and many of the classical analytical parameters.