A distribution-free procedure for classifying a univariate random variable,z, into one of two populations on the basis of a sample of sizeN, in whichmmembers are classified into one population and the remaining (N–m) into the other, is given as follows: Lett(z) =k(z) –h(z), wherek(z) is the number of observations from the first population which are less thanzandh(z) is similarly defined for the second population. Ifz≦ ζ*, where ζ* is that value ofzfor whicht(z) is a maximum, classifyzinto the first population, otherwise into the second. The probability of correct classification, and its estimate, [N–m+t(ζ*)]/N, both converge in probability to the maximum attainable probability of correct classification.