Forecasts of US presidential elections have gained considerable attention in recent years. However, as became evident in 2016 with the victory of Donald Trump, most of them consider presidential elections only at the national level, neglecting that these are ultimately decided by the Electoral College. In order to improve accuracy, we believe that forecasts should instead address outcomes at the state-level to determine the eventual Electoral College winner. We develop a political economy model of the incumbent vote share across states based on different short- and long-term predictors, referring up to the end of the second quarter of election years. Testing it against election outcomes since 1980, our model correctly predicts the eventual election winner in 9 out of 10 cases – including 2016 –, with the 2000 election being the exception. For the 2020 election, it expects Trump to lose the Electoral College, as only 6.2 percent of simulated outcomes cross the required threshold of 270 Electoral Votes, with a mean prediction of 106 Electoral Votes.