We performed a predictive analysis based on Quantitative Structure-Activity Relationships (QSAR) of a very important property of flavonoids which is the inhibition (IC50) of influenza H1N1 virus neuraminidase. The best linear model constructed from 20 molecular structures incorporated four molecular descriptors, selected from more than a thousand geometrical, topological, quantum-mechanical and electronic types of descriptors. The obtained model suggests that the activity depends on the electric charges, masses and polarizabilities of the atoms present in the molecule as well as its conformation. The model showed good predictive ability established by the theoretical and external test set validations.