Integrating Digital Twin (DT) and Explainable Artificial Intelligence (XAI) technologies in critical infrastructures is very important, especially regarding security and efficiency in industrial control systems. Although digital transformation increases complexity in critical systems such as energy, transportation, and healthcare, the security of these systems is also becoming more threatened. DTs provide real-time monitoring and predictive analysis by creating digital copies of physical systems. On the other hand, XAI makes the decisions of artificial intelligence models transparent and allows operators to understand how the system works. These two technologies are usually used separately in the literature, but their integration is limited. This deficiency is addressed by developing a hybrid model that combines DT and XAI technologies. This model aims to increase the accuracy of anomaly detection in critical infrastructures and ensure the system’s transparency and security. While the DT detects deviations in the physical system, XAI is used to explain the reasons for these deviations. In addition, the model is designed to enable adaptive learning and system improvement processes by using a real-time feedback loop to ensure Cyber Resilience (CR). Integrating DT and XAI is an important step that can contribute to future research and applications.