A probabilistic model is offered for tracing the fate of vegetation communities in fire-prone lands that are subjected to regular fuel reduction burning. The model is based on the semi-Markov process (an extension of Markov chain modelling). The inputs necessary for the semi-Markov process are shown to be readily available, familiar -to managers, or at worst, cheap and easy to procure. By manipulation of the probabilities associated with the occurrence of low intensity prescribed fires (i.e. simulating different fire free periods), managers will be able to use readily available data to predict the long term effects of prescribed fire regimes in relation to management goals, especially where maintenance and protection of rare and endangered vegetation communities are major considerations. The model can be used to determine mean times to episodic local extinctions of vegetation types, mean return times for naturally occurring fires, equilibrium proportions of vegetation types within a system at chosen planning horizons, and, by ascribing monetary (or other) values to activities associated with fuel reduction burning and fighting wildfires, to optimize the cost of entertaining the potentially conflicting goals of hazard reduction and conservation. A case study from northeast Victoria is given to illustrate the construction of the components of the model for the fate of the understorey in open-forest which is currently burnt on a regular rotation by the managing authority. A further case study from the malice of central New South Wales is presented as a worked example of how the semi-Markov process could be used in decision support systems aimed at achieving conservation goals.