This paper proposes an approach to model order reduction of stable linear time-invariant (LTI) models. The proposed approach extends time-domain moment matching by the minimization of the ${\mathcal{H}_\infty }$ norm of the error dynamics characterizing the difference between the full-order and reduced-order models given fixed interpolation points. The optimal ${\mathcal{H}_\infty }$ moment matching problem is a constrained optimization problem with bilinear constraints. Introducing a novel numerical procedure, we minimize the approximation error, while respecting the constraints and, thereby, find a suboptimal ${\mathcal{H}_\infty }$ reduced-order model. The effectiveness of the approach is illustrated in a numerical example.