Fungi are serious pathogens for many plants and crops, potentially causing severe economic loss. Early detection and identification of these pathogens is crucial for their timely control. Currently existing methods available for identification of fungi are time consuming, expensive and not always very specific. We used Fourier Transform InfraRed spectroscopy (FTIR) attenuated total reflectance (ATR), combined with Principal Component Analysis (PCA), and Linear Discriminant Analysis (LDA), for differentiating fungal phyto-pathogens at the isolate level. Four different fungi genera were investigated; Colletotrichum, Verticillium, Fusarium and Rhizoctoniai. Our main goal was to differentiate these fungi samples at the level of isolates, based on their infrared (IR) fingerprint absorption spectra. Based on our computerized and objective analyses, our results are in high compliance with existing biological classification methods. FTIR, combined with advanced computerized methods, provides an inexpensive and reagentfree technique that delivers accurate results on fungi classification within few minutes. FTIR may also turn out to be an important in situ and in vivo alternative diagnostic tool in agricultural. At the generic level, the identification success rate was 97.5% using five principal components (PCs), while at the isolates level the identification success rates were 97.1%, 90%, and 89%, respectively, for Verticillium dahliae, Colletotrichum coccodes, and Fusarium oxysporum.