Burnishing is used as the final operation in machining, and brings along advantages such as increase of hardness, resistance against material fatigue and abrasion resistance on the workpiece on which it is applied. Improving the surface roughness of workpiece, improvements on the surface hardness, increase of the abrasion resistance of the material, decreasing depths on the material surface which may cause cracks, etc., directly depend on parameters such as progression, number of passes, press amount and ball diameter used in burnishing operation. For this study, an apparatus was designed which has different heads for a burnishing operation of rotary pieces. The surface of an Al 6061-T6 alloy was subjected to a respective burnishing operation and the effect of the parameters (i.e., pressure force, progression, number of passes and ball diameter) used in the burnishing operation on the surface roughness and surface hardness was determined. In addition, an artificial neural network (ANN) and an adaptive neuro-fuzzy interference system (ANFIS) model are developed for these parameters. Both models provide accurate results that are comparable to the experimental results. However, the ANFIS based model appears more accurate, compared to the ANN based model with respect to the same conditions for the surface roughness and surface hardness.