We present a method of classifying a pattern using information furnished by a ranked list of templates, rather than just the best matching template. We propose a parsimonious model to compute the class-conditional like lihood of a list of templates ranked on the basis of their match scores. We discuss the estimation o f parameters used in the model. The results of maximum likelihood classification on isolated digit patterns consistently show a 10-20\% relative gain in recognition accuracy when we use more than one top-te mplate.