This paper considers an extension of R-optimality to model-robust optimal design, where a prior probability is set on a class of candidate linear models. A generalization of Elfving’s theorem is proved, which gives a geometrical characterization of model-robust R-optimal designs. An equivalence theorem is presented and used to check optimality of designs in a few illustrative examples.