In this study, a QSAR investigation was carried out on a set of thirty-eight isothiazole derivatives targeting NS5B inhibition and thus the treatment of hepatitis C virus (HCV). The research methodology used various statistical techniques, including multiple linear regression (MLR) and artificial neural networks (ANN), to develop models that were satisfactory in terms of internal and external validation parameters, indicating their reliability in predicting the activity of new inhibitors. As a result, a series of potent NS5B inhibitors were designed and their inhibitory potential was confirmed by molecular docking simulations. In addition, these newly formulated compounds exhibited favourable ADMET characteristics, with molecular dynamics studies revealing a stable energy state and dynamic equilibrium. Our work highlights the importance of NS5B inhibition for the treatment of HCV.