Metamodels are effective for providing fast-running surrogate approximations of product or system performance. Because these approximations are generally based on continuous functions, they can provide poor Ž ts of discontinuous response functions. Many engineeringmodels produce functions that are only piecewise continuous, due to changes in modes of behavior or other state variables.Theuse of a state-selecting metamodeling approach that provides an accurate approximation for piecewise continuous responses is investigated. The proposed approach is applied to a desk lamp performance model. Three types of metamodels, quadratic polynomials, spatial correlation (kriging) models, and radial basis functions, and Ž ve types of experimental designs, full factorial designs, D-best Latin hypercube designs, fractional Latin hypercubes, Hammersley sampling sequences, and uniform designs, are compared based on three error metrics computed over the design space. The state-selecting metamodeling approach outperforms a combined metamodeling approach in this example, and radial basis functions perform well for metamodel construction.