In this study, the friction stir technique is proposed to process AZ61 alloy and artificial neural network is built to predict and compare the experimental wear results. The effects of different processing parameters, including spindle speed (800–1200 rpm), travelling speed (05–15 mm/min), and depth of press (0.8-1.2 mm) on the microstructural evolution, mechanical properties and wear behaviour investigated. The grain size of the FSP1 samples found to be 14 ± 2 µm and shifting of peaks are observed in the X ray diffraction analysis chiefly due to texture development. As the spindle speed, travelling speed increases the surface roughness increases, it is observed that Ra – for FSP1 and FSP9 is found to be 68.4 nm and 116.3 nm respectively. Highest micro-hardness (113.36 Hv) values were observed for FSP1 sample and least is FSP9 sample (79. 51 Hv) and BM sample (65.92 Hv). Due to increased heat input into the processed regime, the hardness decreased as rotational and traveling speed increased, resulting in the development of coarse microstructure and a reduction in hardness. Based on wear results it has been observed that specimen FSP1 sample (0.003 g and 0.28) had the lowest weight loss and COF values compared to other FSP conditions. This is due to the combination of process parameters resulted in sufficient heat generation, grain refinement, and strain hardening of the stir zone, which enhanced the wear resistance of the specimen. Coefficient of friction is reduced to 0.28 from 0.68, and weight loss has been reduced to about 58% as compared to BM sample. This work shows that enhancing the wear resistance of magnesium alloys using friction stir processing is a successful approach.