Fungi are microorganisms that are divided into groups and subgroups according to their similarity, genera, species, and strains. Fusarium is considered a phytopathogen that attacks variety of crops throughout the world, causing diseases resulting in severe economic losses. Many of the Fusarium species cause similar symptoms, making it impossible to distinguish among them based on symptoms alone. Fungicides are commonly the most effective treatment of these pathogens, and their use is effective and could prevent or decrease its severity and spread when detected early. Currently, classical methods (microbiological, molecular) are time-consuming. In this study, we aimed to distinguish among three different groups: Fusarium oxysporum, Fusarium solani, and a mixture of both species. Thus, we used Fourier transform infrared microscopy combined with principal component analysis (PCA) and linear discriminant analysis (LDA) classifier. Using the first ten PCs, our classification results showed a 94% success rate in distinguishing among the three groups.