A machine learning approach was applied to geochemical analysis of nine obsidian blades discovered in the archaeological site of Tulūl al-Baqarat (4th millennium BCE, Iraq), aiming at unraveling the provenance of the natural material (volcanic glass, obsidian) employed for carving the studied tools. To accomplish this, we measured the geochemical composition of each archaeological tool to characterize the material, using non-invasive and non-destructive techniques. The obtained data were compare