Trajectory optimization has proven to be a powerful tool in solving a wide variety of optimal control problems in the aerospace field. However, in many cases, numerical complexities prevent the analysis of optimal trajectories for high-fidelity models, particularly due to the inherent difficulty of transcribing high-order dynamic systems. This research project proposes a methodology incorporating reduced-order modeling that retains the most critical dynamic characteristics from a full-order model while allowing the resulting simplification to be manageable for a trajectory optimization solver. The study applies this methodology to evaluate optimal landing trajectories for the UNIFIER19 C7A, a hybrid-electric aircraft equipped with a distributed electric propulsion system that was previously developed under the UNIFIER19 project. Results show that the reduced-order models generated for the aircraft can be used to generate flyable trajectories, verified by tracking the resulting landing approach paths using the base high-fidelity model. It is envisioned that this methodology will also be applicable to other aircraft models and mission phases.