We hypothesized that multiplicative decomposition would improve accuracy only in certain conditions. In particular, we expected it to help for problems involving extreme and uncertain values. We first reanalyzed results from two published studies. Decomposition improved accuracy for nine problems that involved extreme and uncertain values, but for six problems with target values that were not extreme and uncertain, decomposition was not more accurate. Next, we conducted experiments involving 10 problems with 280 subjects making 1,078 estimates. As hypothesized, decomposition improved accuracy when the problem involved the estimation of extreme and uncertain values. Otherwise, decomposition often produced less accurate prediction.