Droplet size, as one of the critical factors that influences spray performance and drift, must be considered when selecting spray nozzles and operational setups. Characterizing a spray nozzle for droplet size is typically completed by evaluating only a select few nozzle types, sizes, and spray pressures, which typically do not provide detailed droplet size information for the entire operational space. This research proposes a structured, experimental design that allows for the development of computational models for droplet size based on any combination of a nozzle's potential operational settings. Ten nozzles with two operational settings (orifice and pressure) and one with three (orifice, pressure, and tip) were evaluated using a response surface experimental design. All models showed high levels of fit to independently collected droplet size data. The computational models were integrated into a spreadsheet-based user interface that allows convenient droplet size predictions for a given nozzle setup. The developed models also allowed for a detailed analysis of each nozzle's entire operational space thereby providing users with a screening tool based on desired droplet size classification. The use of the proposed experimental design provides for efficient nozzle evaluations that can be used to determined droplet size and classification for any combination of operational settings.