The integration of explainable intelligence in digital twins offers significant advantages by enhancing transparency, trust, and informed decision-making across various domains, including manufacturing, healthcare, transportation, and smart cities. By combining real-time data with AI-driven analytics, digital twins enable predictive maintenance, process optimization, transparent communication, and intelligent automation. Despite their transformative potential, these technologies also introduce critical challenges related to AI bias, scalability of explainable methods, and the balance between performance and interpretability. To address these issues, the International Conference on Explainable Intelligence in Digital Twins (EIDT) was established as a dedicated forum for researchers and practitioners to exchange ideas, foster collaboration, and advance trustworthy and interpretable AI-driven systems. EIDT aims to promote cutting-edge research and real-world applications that support the next generation of explainable intelligence in digital ecosystems and intelligent networks.