To answer the increasingly common question I receive, “Will FDA regulate my digital twin?”, it must first deconstruct it into two foundational inquiries:(1) What is the physical asset being twinned? and(2) What is the context of use for the digital twin? From there, one must also ask whether a digital twin is necessary for that context of use, or whether a simpler computational model or AI-enabled simulation may suffice. Understanding this distinction is critical to determining when a digital twin crosses into regulatory oversight. This presentation will review the current landscape of tools and technologies being referred to as digital twins across the life sciences—from mechanistic organ models and AI-augmented simulations to population-scale synthetic patient cohorts. A Digital Twin Maturity Model will be presented for community input, which characterizes levels of maturity across the different components of a digital twin. Finally, we will propose a framework for mapping digital twin maturity to the existing regulatory ecosystem, highlighting how current FDA guidance documents can be leveraged to determine when and how a digital twin may fall under regulatory purview. The goal is to provide a shared vocabulary and practical structure to help developers, sponsors, and regulators navigate the evolving landscape of digital twins in biomedical research and healthcare.