The objective of the study was to define and then evaluate an early decision indicator (EDI) trigger that operated within the first 5 weeks of a response that would indicate a large outbreak of FMD was developing, in order to be able to inform control options within an adaptive management framework. To define the trigger, a previous dataset of 10,000 simulated FMD outbreaks in New Zealand, controlled by the standard stamping-out approach, was re-analysed at various time points between days 11–35 of each response. The two predictive metrics adopted comprised the mean third quartiles of cumulative numbers of infected premises (IPs) at weekly time points, and estimated dissemination rate (EDR) values indicating sustained spread, specifically > 2.0 between days 11-14 or > 1.5 at any time point between days 15–35 of the response. To evaluate the trigger, the trigger was parameterized within the InterSpread Plus modelling framework, and a new series of simulation generated. The trigger was treated like a series of diagnostic tests that were applied during days 11–35 of each simulated outbreak, and its results recorded and then compared to the final size of each outbreak. The performance of the test was then evaluated across the population of outbreaks, and the sensitivity (Se), specificity (Sp), positive predictive value (PPV) and negative predictive value (NPV) calculated. The Se, Sp, PPV and NPV for predicting large outbreaks were 0.997, 0.513, 0.404 and 0.998 respectively. The study showed that the complex EDI incorporating both the cumulative number of IPs and EDR was very sensitive to detecting large outbreaks, although not all outbreaks predicted to be large were so, whereas outbreaks predicted to be small invariably were small. Therefore, it shows promise as a tool that could support an adaptive management approach to FMD control.