Geopolitical context or climate change induced more and more disasters in the two last decades. Particularly, Critical Infrastructures (CI - e.g., water distribution, health care) that support the daily life of societies are impacted by these disasters. These CI are indeed essential. By their various interactions and links, they become more fragile when facing complex situations. For instance, a local event, occurring in a CI (e.g., an accident), can propagate throughout these interactions, impacting other CI, leading to a higher intensity and to a global impact. Classical risks analysis is limited in terms of global and dynamic vision of these CI, to manage these events efficiently and to recover to an acceptable functioning state for the end users. To this purpose, resilience is a useful concept, highlighted by numerous research works and organizations to characterize the best way a CI has to react to an undesirable event and avoid, if possible, its propagation. The purpose of this paper is to present the main principles of a methodology to assess and analyze resilience of a CI based on a multi views and systemic model formalized as a digital twin. This work is done in the frame of the project RESIIST supported by the French research agency ANR (Résilience des infrastructures et systèmes interconnectés, 18-CE39-0018-05) to provide scenarios to test and evaluate the proposed methodology.