The transition to electric vehicles (EVs) presents new challenges and opportunities for sustainable transport systems, particularly concerning battery degradation, lifecycle management, and long-term system reliability. While numerous decision-support models exist for vehicle routing, charging infrastructure planning, and investment analysis, few integrate battery aging dynamics into a comprehensive circularity-oriented decision framework. This paper proposes a novel Battery Circularity Decision Support Framework that links operational, tactical, and strategic decision-making with a semi-empirical battery degradation model. The framework enables stakeholders to evaluate the impacts of driving behavior, duty cycles, charging strategies, and thermal environments on battery state-of-health (SoH), extending into future reuse, repurposing, and recycling pathways. Drawing on recent literature and experimental data, we highlight how various decisions, ranging from energy-efficient routing to battery end-of-life planning, can be informed through degradation-aware simulations. To demonstrate the practical utility of the framework, we apply it to a real-world use case involving an electric bus operating in Sweden. The framework enabled the evaluation of battery degradation over time under consistent operational conditions, revealing the projected timeframe during which the bus could continue to reliably perform the same route. As SoH decreased, the framework supported a strategic decision to reassign the bus to a less power-demanding route, thereby extending its operational life and reducing the risk of service interruptions. This example illustrates how our framework enables data-driven decisions that align with circular economy goals and sustainable fleet operations. By integrating battery aging into system-level planning, the framework fills a crucial gap in current EV battery management and battery circularity methodologies.