Michael S. Wheatland School of Physics, University of Sydney Bayesian refinement of solar flare prediction Wednesday 17th, March 14:05-15:55pm, Carslaw Building Room 359. A number of methods of flare prediction rely on optical classification of sunspots associated with an active region, and historical rates of flaring for a given classification. However these methods largely ignore how many flares the active region has already produced, which is an important indicator to future flare production. In this talk a Bayesian approach to flare prediction is presented, which uses the past history of flaring of an active region to refine an initial prediction for flaring, which e.g. may come from one of the extant prediction schemes. The theory of the new method is outlined, and simulations are presented to show how the refinement step works in practice. Prospects for practical implementation of the method with solar data are also discussed.