The brain is a highly complex system whose functioning is critical for our interaction with the world. Neural elements, from single cells to brain systems, constantly fluctuate in their dynamics, accompanying the plethora of possible exchanges between our environment and ourselves. However, sometimes things go awry. An unfortunate example is post-traumatic stress disorder (PTSD), a debilitating clinical condition that can appear after exposure to a threatening life event. In this work, using complexity as a framework, we aim to introduce the dynamic brain network model of PTSD. We hope this model will allow the generation of novel specific hypotheses concerning brain organization and dynamics in PTSD research. We first introduce how the network framework complements the localizationist approach centered in specific brain regions or subsets of brain regions, with a whole brain approach considering brain regions’ dynamic relationships. Then, we review key concepts in network neuroscience, focusing on the importance of the network topology and dynamics to understand the organizational principles of the brain, that is, functional segregation and integration. In the third part, we apply this knowledge to describe the possible trajectories conducting a brain system to present PTSD alterations. Accordingly, we introduce the Dynamic Brain Network Model (DBNM) of PTSD, a concrete framework built on the network approach and resilience theory to study the transition of a brain network from state 1 ( e.g. , before the traumatic event) to state 2 ( e.g. , after the traumatic event). To conclude, we provide a summary of metrics for quantifying elements on the DBNM and its potential use in computational models of PTSD.