Polyphenolic compounds are considered to have a major impact on the quality of red wines. Sensory perception, such as astringency and bitterness, are mainly related to condensed tannin, while colour intensity and evolution is due to anthocyanin composition. Therefore, the quick analytical measurement of phenolic compounds appears to be a real challenge for wine monitoring. Fourier transform infrared (FTIR) and ultraviolet-visible (UV-vis) spectroscopy with chemometrics are good candidates for predicting polyphenolic contents in wines, but they have not yet been compared in terms of efficiency of each wavelength area. Thus, the possibility of combining the two areas has not been investigated. This work sought to determine the tannin and anthocyanin content of ninety-two wines. The wine selection covered different vintages, varieties and regions. Tannin concentration was analysed by precipitation with protein and polysaccharide and by the Bate-Smith assay. Free anthocyanin concentration was analysed by bisulfite bleaching and the monomers/polymers ratio was analysed using the Adams-Harbertson method. Molecular anthocyanin concentration was also obtained by HPLC/UV-vis. Two spectra were collected using UV-vis and FTIR devices. The data collected were statistically analysed using the partial least squares (PLS) regression method. The correlations obtained were relevant to both of the spectrum areas studied, with a coefficient of determination for cross validation larger than 0.7 for most parameters studied. While the two spectroscopic methods gave almost identical results, FTIR indicated higher robustness for the prediction of tannin concentration. Conversely, UV-vis appeared to be more relevant when determining anthocyanin concentration and evolution. Finally, the models obtained when combining the two spectrum areas gave slightly better results. When a selection of different visible wavelengths were added to the FTIR spectrum, the results showed that the prediction of anthocyanin parameters improved considerably, thus highlighting the importance of the visible area when estimating these compounds.