Multivariate statistical models were utilized to identify the interaction between the inhibitory activity and the molecular properties of the different antimycotics against Microsporum canis. Information on the inhibitory potency against M. canis and molecular properties of antifungal agents were obtained from literature. The relationship between the inhibitory potency and the molecular properties of the different antimycotics against M. canis was established using multiple linear regression analysis (MLRA) and principal component analysis (PCA). Three major descriptors: topological polar surface area, molecular weight, and rotatable bond count of the antimycotics were identified to confer inhibitory action against M. canis using MLRA (r²=0.8968, p<0.0001) and PCA (95.86% total contribution rate). Both MLRA and PCA as statistical approaches demonstrate their potential as tools in computational structure design and for possible synthesis of next generation antimycotics as more effective treatments of fungal infections.