This paper proposes an efficient approach to generate macromodels for simulating microelectromechanical systems using an experimental design and fuzzy logic model (FLM). Various approaches using force and energy macromodels to perform coupled simulations are proposed. Then, an experimental design is utilized to reduce the number of data needed for . macromodel identification, and an FLM is chosen for fitting the data. The identification scheme involves cluster estimation to determine the FLM structure, and backpropagation method to efficiently find the FLM structure parameters leading to accurate macromodels. The algorithm has been applied to a magnetic microactuator. Comparing with full meshed static coupled simulation shows force macromodel yielded errors of less than 1.5% for a 5μm displacement. And, the dynamic coupled simulation takes only several minutes. The results demonstrate the efficiency and effectiveness of the proposed approach.