Metallurgical digital twins have demonstrated success in optimising the processing performance of operational plants by integrating ore characteristics, material flows, process data and plant constraints. First-principles modelling techniques are particularly valuable for explaining process behaviour, including the planning stages of new plants or expansion of existing ones. This study presents a comprehensive model of a gold processing site at Rupert Exploration Finland’s greenfield Ikkari gold project in northern Finland. The model encompasses the minerals processing plant, including SAG mill, ball mill and gravity concentrator, the hydrometallurgical plant, including carbon-in-leach, cyanide destruction, carbon reactivation and electrowinning, and the water treatment plants, including ion exchange, reverse osmosis, gypsum precipitations and crystallisation. Leveraging advanced modelling techniques, a flexible simulation was developed with adjustable parameters to replicate the processes in accordance with various feed compositions, equipment performances and operation strategies. The simulation model incorporated the available experimental data from laboratory tests as well as the empirical knowledge of several subject matter experts. The key findings and critical operational insights of utilising such a comprehensive model enabled the identification of optimal treatment strategies for targeted orebodies, evaluation of multiple design scenarios and alignment to operational requirements for Ikkari Project. In addition, the model evaluated hundreds of process variables throughout the process plants, providing better understanding of the overall process complexity through the detailed description of its interconnected parts. Finally, it discusses the application of metallurgical digital twins in early-stage engineering, highlighting the insights it can provide in obtaining environmental permits, resource planning, ore blending, among other benefits.