We develop a maximum-likelihood (ML) approach based on option markets for estimating structural models. We use dynamic programming and finite elements, derive the likelihood function, and, then, simultaneously solve and estimate the setting. We conduct a case study on Ford at the end of 2006, when the carmaker experienced financial difficulties. The stock- and the option-based ML output similar credit-risk parameters. Both align with rating agencies assessments.