A probabilistic approach to the brain image matching problem is proposed in which no assumptions are made about the nature of the intensity relationship between the two brain images. Instead the correspondence between the two intensities is represented by a conditional probability, which is iteratively determined as part of the matching problem. This paper presents the theory and describes its finite element implementation. The results of preliminary experiments indicate that there remain several aspects of the algorithm that require further investigation and refinement.