Display omitted •PMMA nano-fiber membrane diameter modeled by artificial neural networks (ANN).•ANN model predicted fiber diameter at new instances.•The model provided process window for the desired fiber diameter.•ANN model identified the importance of process parameters on fiber diameter.•Graphical user interface of the ANN model is designed. Relationship between the electrospun fiber diameters of poly(methyl methacrylate) (PMMA) nanofibers with process parameters are complex and nonlinear. We used artificial neural networks technique to estimate the electrospun PMMA nanofiber diameter as a function of polymer concentration, nozzle-collector distance, temperature, flow rate, and voltage. The average errors of the predicted fiber diameters for training and testing data were found to be 1.26% and 5.74%, respectively. Process window for optimum nanofiber diameter was generated. The proposed index of relative importance, evaluated in this study, will be a useful guide to quantitatively and qualitatively identify and define the importance of different electrospinning parameters on the fiber diameter.