A total of 25 sugarcane spirit extracts of six different Brazilian woods and oak, commonly used by cooperage industries for aging cachaça, were analyzed for the presence of 14 phenolic compounds (ellagic acid, gallic acid, vanillin, syringaldehyde, synapaldehyde, coniferaldehyde, vanillic acid, syringic acid, quercetin, trans-resveratrol, catechin, epicatechin, eugenol, and myricetin) and two coumarins (scopoletin and coumarin) by HPLC-ESI-MS n. This data was compared with the previous one obtained from HPLC-DAD-Fluorescence. Pending questions regarding to epicatechin attribution, galic acid and elagic acid co-elution have been solved through HPLC-ESI-MS n analysis. Furthermore, an HPLC-DAD chromatographic fingerprint was build-up using chemometric analysis based on the chromatographic elution profiles of the extracts monitored at 280 nm. The main difference observed among oak and Brazilian woods remains in the concentration of coumarin, catechin, syringaldehyde, and coniferaldehyde. The chemometric analysis of the quantitative profile of the 14 phenolic compounds and two coumarins in the wood extracts provides a good differentiation between the Brazilian wood and oak extracts. The chromatographic fingerprint treated by multivariate analysis revealed significant differences among Brazilian woods themselves and oak, clearly defining six groups of wood extracts: (i) oak extracts, (ii) jatobá extracts, (iii) cabreúva-parda extracts, (iv) amendoim extracts, (v) canela-sassafrás extracts and (vi) pequi extracts. Multivariate analyses of UV-Vis spectral data from 93 cachaça wood extracts provide a simple and robust model to classify aged Brazilian cachacas according to the wood species used in the maturation barrels. Application of PCA (Principal Components Analysis) and Abstract iv HCA (Hierarchical Cluster Analysis) leads to identification of 7 clusters of cachaca's wood extracts (amburana, amendoim, balsamo, castanheira, jatoba, jequitibá and oak). LDA (Linear Discriminant Analysis) affords classification of 10 different wood species used in the cachaça extracts (amburana, amendoim, balsamo, cabreuva-parda, canela-sassafras, castanheira, jatobá, jequitiba-rosa, louro-canela, and oak) with an accuracy ranging from 80% (amendoim and castanheira) to 100% (bálsamo and jequitibá-rosa).This model self consistency was checked using 50 samples of commercial cachaças. A very good classification was observed for this model, which 100 to 80% of correct assignment. The methodology provides a robust low-cost alternative to methods based on liquid chromatography and mass spectrometry to classify cachaças aged in barrels that are composed of different wood species. Furthermore, it holds some potential as a possible forensic tool for wood identification which could be applied to control the wood marked of endangered species. Our findings could be extended to other spirits and to a wider variety of wood species.