This paper presents a maximum likelihood estimator for term structures of conditional corporate default probabilities, incorporating the dynamics of firm-specific and macroeconomic covariates. Using data on over 2700 U.S. industrial firms from 1979 to 2004, the authors find that the level and shape of the estimated term structure of conditional future default probabilities depend on a firm's distance to default (a volatility-adjusted measure of leverage), trailing stock returns, trailing S&P 500 returns, and U.S. interest rates. Distance to default is the most influential covariate, with default intensities decreasing as short-term interest rates rise. The model's out-of-sample predictive performance is superior to other available models. The authors also discuss the application of their model in credit risk analysis, risk management, and regulatory contexts.This paper presents a maximum likelihood estimator for term structures of conditional corporate default probabilities, incorporating the dynamics of firm-specific and macroeconomic covariates. Using data on over 2700 U.S. industrial firms from 1979 to 2004, the authors find that the level and shape of the estimated term structure of conditional future default probabilities depend on a firm's distance to default (a volatility-adjusted measure of leverage), trailing stock returns, trailing S&P 500 returns, and U.S. interest rates. Distance to default is the most influential covariate, with default intensities decreasing as short-term interest rates rise. The model's out-of-sample predictive performance is superior to other available models. The authors also discuss the application of their model in credit risk analysis, risk management, and regulatory contexts.