One of the important prerequisites for efficient design optimization of microwave structures is availability of fast yet reliable replacement models (surrogates) so that multiple evaluations of the structure at hand can be executed in reasonable timeframe. Direct utilization of full-wave electromagnetic (EM) simulations for handling optimization-related tasks is often prohibitive. A popular approach to construction of fast surrogates is data-driven modeling. Unfortunately, it normally requires a large number of training samples, and it is virtually infeasible for structures that exhibit highly nonlinear responses (e.g. filters or couplers). In this work, a design-oriented modeling technique is proposed where good accuracy is achieved by careful non-uniform design space sampling that accounts for nonlinear relationship between the operating frequency of the structure and its geometry parameters, as well as carrying out the modeling process only for selected characteristic points of the structure responses (those that determine satisfaction/violation of given design specifications). Our approach is demonstrated using a miniaturized microstrip rat-race coupler modeled in a wide range of geometry parameters and compared to conventional data-driven modeling using kriging interpolation. Design optimization examples are also provided. Copyright (c) 2016 John Wiley & Sons, Ltd.