Presidential election forecasting models may miss the mark, sometimes grossly, as the 1992 contest demonstrated. The reason for this, we argue, is specification error. The models include irrelevant variables and exclude relevant ones. In particular, prospective voting variables have been ignored. When prospective economic and political evaluations are added, alongside traditional retrospective evaluations, forecasting quality improves sharply. These full-time forecasting models that tap voter onentations toward the future, as well as toward the past, promise long-run accuracy gains.