This presentation presents a non-destructive, empirical and replicable method for aging bison teeth. Tooth eruption, growth, and attrition can document age-at-death, which informs on hunting strategies, occupation seasonality, environmental conditions, and herd health. Previous dentition studies utilize numerous tooth metrics that commonly require specimen-destructive research methods. Also, occlusal wear age estimates rely on subjective wear patterning classifications and figures. We suggest a new approach that provides age profiles by “mapping” occlusal wear with ESRi’s AcrGIS software. Planview mandibular tooth photos from the University of Wyoming’s known-age mandible sample, and well-documented prehistoric samples including the Agate Basin, Hawken, Horner, Glenrock, and Vore sites were captured and georeferenced. Next, GIS polygons were digitized for various occlusal surface features. Digitized GIS shape files were then used to generate various occlusal surface feature areas, and multiple statistical methods were employed that explore relationships between quantified occlusal surfaces and specimen ages.