Gallium, germanium, and indium are critical minerals used in a variety of high-tech applications, net- zero emissions technologies and defence technologies, including semiconductors, solar cells, touchscreens and fibre optics. These elements are typically recovered as 'by-products' during the processing of major commodities such as aluminium and zinc. The association of gallium with bauxite, and germanium, indium and gallium with sphalerite in zinc ores is well described; however, the total resource endowment of these elements in mineral deposits at the national-scale is currently unknown. Under standard mineral resource reporting codes such as the JORC Code, companies are obligated to report only those commodities material to the overall economic extraction of the deposit. as a result, elements produced as by-products are often overlooked in public announcements and are rarely publicly reported as part of a mineral resource. However, there is an increasing need for decision-makers to understand the potential national inventory of these commodities to prioritise resource development and establish domestic supply chains. To address this knowledge gap, Geoscience australia has developed a predictive methodology based on mineral system knowledge and mineralogical associations, using random forest-based machine learning algorithms, to estimate the in situ resources for gallium, germanium, and indium in australian zinc deposits. Using this methodology, a by-products reporting tool to aid decision-makers and industry is under development. The tool will produce aggregate figures at a national-scale and report by-product estimates at the deposit-scale against known mineral systems and mineralogy. This will allow for an enhanced understanding of potential by-product production and will guide downstream processing requirements. This capability establishes a foundation for future analytical techniques to estimate by-products in ores for a range of other commodities and mineral systems, and will improve national resource inventory estimates for critical minerals.