Accurate Candida species identification remains a challenge due to their phenotypic and genotypic similarity. Species belonging to the ∗psilosis group, are even described as phenotypically indistinguishable. Also, most of the genotypic methods commonly used to discriminate these species are laborious and very expensive. In this work we developed a Fourier-transform infrared spectroscopy with attenuated total reflectance (FTIR-ATR) based method as a reliable alternative for the discrimination of 12 Candida species. The collection comprises 82 clinical isolates obtained from distinct biological products, recovered between 2007 and 2014 in Portugal and Brazil and previously characterised by CHROMagar Candida and PCR-based sequencing techniques. Infrared spectra were analysed with principal component analysis (PCA) and partial least squares discriminant analysis (PLSDA). The results demonstrated that the 12 species could be successfully discriminated using the proposed infrared spectroscopy based method. Noteworthy, the PLSDA model led to the correct identification of 99.6% of the analysed clinical isolates. This rapid, low cost, and environmental friendly technique proved to be a reliable alternative for the identification of Candida species that share many phenotypic and genotypic characteristics and are often difficult to distinguish.