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In recent years there has been increased demand for readiness and availability metrics across many industries and especially in national defense to enable data‐driven decision making at all levels of planning, maintenance, and operations, and in leveraging integrated models that inform stakeholders of current operational system health and performance metrics. The digital twin (DT) has been identified as a promising approach for deploying these models to fielded systems although several challenges exist in wide adoption and implementation. Two challenges examined in this article are that the nature of DT development is a system‐specific endeavor, and the development is usually an additional effort that begins after initial system fielding. A fundamental challenge with DT development, which sets it apart from traditional models, is the DT itself is treated as a separate system, and therefore the physical asset/DT construct becomes a system‐of‐systems problem. This article explores how objectives in DT development align with those of model‐based systems engineering (MBSE), and how the MBSE process can answer questions necessary to define the DT. The key benefits to the approach are leveraging work already being performed during system synthesis and DT development is pushed earlier in a system's lifecycle. This article contributes to the definition and development processes for DTs by proposing a DT development model and path, a method for scoping and defining requirements for a DT, and an approach to integrate DT and system development. An example case study of a Naval unmanned system is presented to illustrate the contributions. [ABSTRACT FROM AUTHOR]