The Department of Defense (DoD) has established the “5G to Next G” initiative to accelerate the use of 5G networks and associated 5G technologies in support of DoD use cases. In particular, the US Marine Corp (USMC) is interested in exploring the suitability of 5G networks and technologies for its expeditionary operations. This paper will present a use case of augmenting the Marine Corps Enterprise Network (MCEN) with 5G capabilities using a Network Digital Twin (NDT) approach to support a Forward Arming and Re-Fueling Point (FARP) mission thread. Currently, FARP missions are supported by legacy VHF/UHF voice communication radios to provide security, command and control. Newer technologies in radars, cameras, and a wide range of short-to-midrange sensors (acoustic, seismic, magnetic, and infrared) can greatly aid FARP mission execution, but they also present significant challenges to communication and coordination during FARP operations. 5G is a promising emerging solution to provide high bandwidth and low latency communications to meet future FARP information exchange requirements driven by increasingly capable sensor deployments to counter advanced threats. Live-virtual-constructive prototyping and experimentation using NDT technology offers significant value to the above use case as it provides for integration of 5G network components with a digital replica of existing network infrastructure such as the MCEN. NDT can provide a high fidelity emulation of the communication network integrated with its operating environment and the application traffic carried by it, leveraging real-world data about a physical network as input and producing accurate predictions regarding how that physical network will be affected by the addition of new capabilities and requirements. Increased network traffic loading from newer radar, electro-optic, infrared and other sensor technologies can then be modeled to better understand their contributions to mission execution while simultaneously evaluating their impacts to existing network infrastructure. This study uses a NDT model