Disasters often result in mass casualty incidents, which trigger a series of complex decisions made at casualty collection points and advanced medical posts. The essential components in a disaster management chain are triage and casualty evacuation. Casualty evacuation without effective coordination may lead to overcrowding at hospitals and result in an increasing number of casualties. Thus, guidance for rapid transportation is needed according to triage categories, needed/available ambulances, human resources, and destination hospital capabilities. At casualty collection points, the process of medical decision-making is very complex as a significant amount of blood can be lost to internal bleeding, for example in the peritoneal, pleural, or pericardial areas, without any noticeable signs. This paper reviews several studies focusing on triage and evacuation guidance for a mass casualty incident (MCI) based on artificial intelligence.