De Ross, J & Cuello, D 2026, 'Towards a deformation-based probabilistic framework for rockburst hazard forecasting in cave mining', in A van As, D Cumming-Potvin & J Wesseloo (eds), Caving 2026: Proceedings of the Sixth International Conference on Block and Sublevel Caving, Australian Centre for Geomechanics, Perth, pp. 1-10, https://doi.org/10.36487/ACG_repo/2645_98 (https://papers.acg.uwa.edu.au/p/2645_98_De_Ross/) Abstract: Rockburst hazard forecasting in cave mining is complicated by the evolving interaction between mininginduced stress redistribution, seismicity and progressive rock mass degradation. Conventional forecasting approaches have largely relied on seismic event metrics, energy-based demand or deterministic numerical modelling, none of which directly represent excavation-scale damage mechanisms or the uncertainty governing damage realisation. This paper presents a deformation-based, probabilistic framework for rockburst hazard forecasting tailored to cave mining environments and grounded in deformation-based support design (DBSD) principles. The approach reframes hazard in terms of the probability of exceeding damage-related deformation thresholds, recognising that pre-existing stress fracturing consumes support capacity prior to dynamic loading. Numerical stress modelling is used to define the evolving stress environment, while Monte Carlo simulation is employed to capture key sources of variability, including rock mass heterogeneity, rupture depth, bulking time, remnant support capacity and seismic efficiency. Application to cave mining case studies demonstrates that damage occurrence correlates with deformation demand exceedance rather than event size. Ultimately, probabilistic forecasting combined with robust operational governance provides a defensible basis for tracking hazard migration and managing strainburst risks as cave geometry and stress conditions evolve. Keywords: rockburst hazard forecasting, deformation-based support design, strainburst, Monte Carlo simulation, cave mining, remnant support capacity