Simulation models are used to design extruders in the polymer processing industry. Thiseliminates the need for prototypes and reduces development time for extruders and, in particular,extrusion screws. These programs simulate, among other process parameters, the temperature andpressure curves in the extruder. At present, it is not possible to predict the resulting melt quality fromthese results. This paper presents a simulation model for predicting the melt quality in the extrusionprocess. Previous work has shown correlations between material and thermal homogeneity and thescrew performance index. As a result, the screw performance index can be used as a target value forthe model to be developed. The results of the simulations were used as input variables, and with thehelp of artificial intelligencemore precisely, machine learninga linear regression model was built.Finally, the correlation between the process parameters and the melt quality was determined, and thequality of the model was evaluated.