This article is about a simple two-variable equation forecasting presidential election outcomes and a three-variable equation forecasting seat change in House elections. Over the past two decades a cottage industry of political forecasting has developed (Lewis-Beck and Rice 1992; Campbell and Garand 2000). At the 1994 meeting of the Southern Political Science Association, several participants offered their forecasts of the upcoming midterm House elections. Unfortunately, not one of the forecasters was within 20 seats of the actual outcome. If, however, these forecasts had been pooled, as Gaddie (1997) points out, then they would have come remarkably close to the actual seat change that occurred. Moving forward, at the 1996 APSA Annual Meeting the collection of forecasters did a much better job with that year's presidential election. The forecasters also got the overall popular vote outcome correct at the 2000 APSA Annual Meeting for that year's presidential election. We all forecasted a victory for Al Gore, with James Campbell coming the closest to the actual total (50.2%) at 52.8%. At the panel at the 2004 APSA Annual Meeting almost every forecaster predicted the actual outcome correctly. Forecasting elections holds us accountable—we cannot go back and change our forecast for an election after it has occurred. Moreover, if we stick with one forecast, it easy to judge the overall accuracy of our equations.