  A Bayesian approach to solar flare prediction has been developed, which uses
only the event statistics of flares already observed. The method is simple,
objective, and makes few ad hoc assumptions. It is argued that this approach
should be used to provide a baseline prediction for certain space weather
purposes, upon which other methods, incorporating additional information, can
improve. A practical implementation of the method for whole-Sun prediction of
Geostationary Observational Environment Satellite (GOES) events is described in
detail, and is demonstrated for 4 November 2003, the day of the largest
recorded GOES flare. A test of the method is described based on the historical
record of GOES events (1975-2003), and a detailed comparison is made with US
National Oceanic and Atmospheric Administration (NOAA) predictions for
1987-2003. Although the NOAA forecasts incorporate a variety of other
information, the present method out-performs the NOAA method in predicting mean
numbers of event days, for both M-X and X events. Skill scores and other
measures show that the present method is slightly less accurate at predicting
M-X events than the NOAA method, but substantially more accurate at predicting
X events, which are important contributors to space weather.
