Budgeting for biodiversity conservation requires realistic estimates of threat abatement costs. However, data on threat management costs are often unavailable or unable to be extrapolated across relevant locations and scales. Conservation expenditure largely occurs without a priori cost estimates of management activities and is not recorded in ways that can inform future budgets or cost-effective management decisions. We provided transparent, broadly applicable cost models for 18 Threat Abatement Strategies aimed at managing the processes threatening Australia's biodiversity. We defined the actions required to implement each strategy and used a consistent structure to classify costs of labour, travel, consumables and equipment. We drew upon expert knowledge and published literature to parameterise each model, estimating the implementation cost of each strategy across the Australian continent, accounting for spatial variables such as threat presence, terrain, and travel distance. Estimated annualised costs for the threat abatement strategies varied considerably between strategies and across Australia, ranging from $24 to $879,985 per km² ($0.24–$8880 per ha). On average, labour was the largest cost component (49%), followed by consumables (37%), travel (13%) and equipment (2%). Based on national scale variables and assumptions, cost estimates across Australia for each threat abatement strategy ranged from +44% and −33% of the most common cost estimate. Policy implications. We provide a consistent and transparent approach to budgeting for threat abatement strategies, aiming to improve conservation planning processes, outcomes, and reporting across Australia. In addition, understanding the budget required to achieve threat management outcomes can aid revenue-raising and target setting. The models, cost layers and estimates we generate provide the basis for a nationally consistent approach for estimating and recording the cost of biodiversity management strategies, which should be continually updated and improved with local-scale information over time.