We show that the space-mapping algorithm, originally developed for microwave circuit optimization, can enable the efficient optimization of nanoplasmonic devices. Space-mapping utilizes a physics-based coarse model to approximate a fine model accurately describing a device. The main concept in the algorithm is to find a mapping that relates the fine and coarse model parameters. If such a mapping is established, we can then avoid using the direct optimization of the computationally expensive fine model to find the optimal solution. Instead, we perform optimization of the computationally efficient coarse model to find its optimal solution, and then use the mapping to find an estimate of the fine model optimal. In this paper, we demonstrate the use of the space mapping algorithm for the optimization of metal dielectric- metal plasmonic waveguide devices. In our case, the fine model is a full-wave finite-difference frequency domain (FDFD) simulation of the device, while the coarse model is based on the characteristic impedance and transmission line theory. We show that, if we simply use the coarse model to optimize the structure without space mapping, the response of the structure obtained substantially deviates from the target response. On the other hand, using space mapping we obtain structures which match very well the target response. In addition, full-wave FDFD simulations of only a few candidate structures are required before the optimal solution is reached. In comparison, a direct optimization using the fine FDFD model in combination with a genetic algorithm requires thousands of full-wave FDFD simulations to reach the same optimal.