Metallurgical test work is the cornerstone of process design, underpinning critical decisions on process flow sheet and equipment selection, reagent dosing, equipment sizing, and overall process performance. Due to the sparse and localised nature of early-stage sampling, estimating metallurgical response consistently across the entire deposit can be challenging. While sampling density does improve as projects advance, ensuring continuity and comparability of test work from early phases of study through to detailed design is critical in developing a reliable and optimised process. This paper introduces a framework for ‘bridging the gap’ between historic and current test work data sets to de-risk and enhance process design. This approach leverages geometallurgical principles by integrating geological data – lithology, alteration, mineralogy, liberation and mineral association – with metallurgical test work response to create a predictive, data-rich foundation for process design. It also highlights the critical role of sample selection and test work program design in reducing technical risk in process design. By incorporating legacy data through structured gap-filling techniques and linking it with current, variability-driven test work, this methodology reduces uncertainty in design and strengthens Mine to Mill integration. It also serves as a driver for process optimisation from concept through to operation. The result is a more robust framework from sampling to design that supports informed decisionmaking and maximises value across the Life-of-Mine.