AbstractWhen the probability of a negative unit contribution is non-negligible, desirable and undesirable data configurations may map into the same breakeven point. In the general case, the decision relevance of a breakeven point probability distribution is rather obscure. Assuming bivariate normality, with a "small" probability of a negative denominator, then an approximation procedure based on the Geary-Hinkley transformation is a convenient and powerful means of obtaining information about the breakeven point probability distribution. Hence, for practical purposes it may be unnecessary to resort to computer simulation or to numerical integration of the complex exact density function of the breakeven point.