This paper presents a program analysis to estimate uncaught exceptions in ML programs. This analysis relies on unification-based type inference in a non-standard type system, using rows to approximate both the flow of escaping exceptions (a la effect systems) and the flow of result values (a la control-flow analyses). The resulting analysis is efficient and precise; in particular, arguments carried by exceptions are accurately handled.