The efficient recovery of uranium from concentrator tailings is a critical objective for hydrometallurgical operations treating complex, variable orebodies. This paper presents the development and initial deployment of a Tails Leach Optimisation Tool for a seven-tank sulfuric-acid uranium leach circuit at an Australian operation. The tool, implemented in MATLAB®, couples a phenomenological chemical-kinetic model of uranium dissolution with dynamic mass and energy balances for a cascade of continuous stirred-tank reactors (CSTRs), allowing each tank in the circuit to be modelled individually (Crundwell, 1995; Vetter, Barker and Turner, 1989). Operational data are imported to identify key uncertainties – most notably, variable feed mineralogy and iron speciation – and to support dynamic model calibration. The calibrated model is then used to simulate plant performance, forecast operational outcomes, and optimise reagent dosing rates and tank temperature set points, subject to practical constraints on acid and oxidant addition, temperature limits and gelling risk. Preliminary application suggests that the approach can increase uranium recovery and improve reagent utilisation by enabling feed-forward, model-based decision support for operators in the presence of long residence times and delayed assay feedback (Niu et al, 2022). The work builds on previous kinetic and reactor-modelling studies of uranium leaching, extending them toward a practically deployable optimisation and control tool for modern tailings leach circuits (Crundwell, 1995; Rubisov and Papangelakis, 2000; Dorfling et al, 2013).