The mechanical characteristics of the aluminium alloy AA 7075, such as its increased ductility and lower fatigue, are well recognized. It is frequently employed in the aerospace sector and is a strong candidate for numerous other technical uses. It is the best option for a variety of applications thanks to its outstanding corrosion resistance. With the help of conventional machining, it is difficult to make complex shaped components. For avoiding these kind of issues, numerous advanced machining methods have been developed. Wire electrical discharge machining (WEDM) is one of them which is the variant of Electrical Discharge Machine (EDM). In this present investigation, an endeavor has been taken to analyze the Wire Electrical Discharge Machining (WEDM) of AA 7075 aluminium alloy with the help of Taguchi’s approach. The study analyzed the various process variables that affect the WEDM process. The results were then analyzed to determine the overall performance of the process. Various performance measures namely material removal rate, surface roughness and tolerance errors were considered in this investigation. ANOVA is the statistical analysis performed to determine the significance of process variables. A hybrid grey-based Artificial Intelligence ANFIS model was used to predict the desired multi performance index. The outcomes of the analysis proved that the model offers effective and precise prediction which will be much helpful for the manufacturer to predict the desired performance measures.