Airline operations experience schedule disruptions every day. These schedule disruptions require intervention from the airline operations controllers through schedule recovery. In a hub and spoke airline network model, a disruption such as a flight cancellation can affect passenger itineraries in multiple fight legs, making it hard for airlines to re-accommodate disrupted passengers within a short time period. The current airline recovery solutions do not explicitly consider passenger recovery. This dissertation investigates the passenger recovery process by considering the challenges faced by passengers during a schedule disruption, the current solutions used to recover disrupted passengers and how a suitable solution can be designed, developed, tested and validated to ensure that it solves these challenges. Data was collected from existing records of flight schedules and passenger bookings. The data collected was used as input to an optimisation model for passenger recovery. Scrum Agile Development methodology was adopted as the software methodology for developing the solution. A proof of concept web application was developed to make passenger recovery easier and reduce operational cost and passenger delay time. An optimization model was developed based on IBM ILOG CPLEX optimiser to help solve disruptions faster. Testing was conducted by both the developer and a selected sample of airline industry users