Free-boundary problems arise when the solution of a PDE and the domain over which the PDE must be solved are to be determined simultaneously. Three classes of stochastic control problems (optimal stopping, singular and impulse control) reduce to such free-boundary problems. Several classical examples including American option pricing and portfolio optimization with transaction costs belong to these classes. This talk describes a computational method that solves free-boundary problems by converting them into a sequence of fixed-boundary problems, that are much easier to solve. We will illustrate application on a set of classical problems, of increasing difficulty and will also see how the method can be adapted to efficiently handle problems in large dimensions.