A number of recent articles have examined the ability of financial variables to predict recessions. In this article, Peter Sephton extends the literature by considering a nonlinear, nonparametric approach to predicting the probability of recession using multivariate adaptive regression splines (MARS). The results suggest that this data-intensive approach to modeling is not a panacea for recession forecasting. Although it does well explaining the data within the sample, its out-of-sample forecasts do not improve upon the benchmark probit specification.