The aircraft dispatch decision is a complex analysis based on many factors related to airworthiness regulations, aircraft health status, resource availability at current and future stop(s) and operational preferences of the operator. Within the turnaround time (TAT) a decision has to be made whether the aircraft can return to service, defects have to be deferred, operational restrictions apply, maintenance has to be performed, or if the aircraft is unable to safely perform the next flight. This paper presents a framework for automated dispatch decision support and, as a first step of implementation of the framework, a proof of concept for automated root cause identification by means of a case study on a Airbus A320 wing anti-ice valve. A decision tree algorithm has been applied to a synthetic dataset, representing historical failure data with associated root causes and observed symptoms, achieving correct classification of the root cause for 40% of the cases. Analysis of the results show that the accuracy of the method increases with an increasing number of symptoms associated to a root cause. Furthermore, the method cannot distinguish between root causes with similar symptoms. Although the use of synthetic data restricts conclusions that can be drawn from the results, the work shows a proof of concept for automated root cause identification and leads to initial findings that are essential for future implementation and optimisation of the method. Eventually, the framework will be operationalised in the form of a mobile tool to assist stakeholders in on-site aircraft dispatch decision support.