Summary: This letter presents robustness bounds (RBs) for receding horizon controls (RHCs) of uncertain systems. The proposed RBs are obtained easily by solving convex problems represented by linear matrix inequalities (LMIs). We show, by numerical examples, that the RHCs can guarantee robust stabilization for a larger class of uncertain systems than conventional linear quadratic regulators (LQRs).