The capability to spatially triage geographical areas as low and high interest has the potential to provide valuable information as forensic intelligence to law enforcement operations, and related provenancing applications. Among others, our previously published work has largely been based on the elemental composition of topsoil samples, omitting other potentially useful compositional characteristics, such as mineralogy, that have proven valuable in forensic casework discriminations. In this contribution, a total of 334 topsoil (0–5 cm sampling depth; 0–75 µm fraction) samples collected from the Canberra region in Australia, were selected from a larger collection (n = 685) and their bulk mineralogy determined using X-ray powder diffraction (XRPD). Utilising an existing casework technique for discriminating soils by mineralogy, a total of twelve diagnostic peaks were selected representing commonly occurring minerals. Peak intensities were normalised relative to the sum of their intensities and used to create an indicative mineralogy dataset for the study region. Based on an existing algorithm for assigning investigative analytical similarities from overlapping areas between two Cauchy distributions, the provenance was estimated for thirteen blind topsoil samples. Provenance maps based on the mineralogy were subsequently combined with earlier elemental-based predictions, incorporating contrasting discriminatory capabilities from both techniques. Results indicate the mineralogical component of topsoils can provide accurate provenance predictions, and when combined with those based on the elemental composition, can further delineate areas as low interest that otherwise would not necessarily be differentiated from one technique alone.