The public transport smart cards offer transit planners access to a tremendous source of spatial-temporal data, offering opportunities to infer a passenger’s mobility pattern and path choices. It is essential to accurately estimate the origin and destination (OD) matrix to understand the travel demand. This research has developed a new approach using a trip chain model to estimate public transport commuter’s trajectories in a multi-legged journey. This research has proposed new algorithms to link the passenger's journeys involving the mode transfers using assumptions relating to the passenger paths in between their successive boarding’s and their acceptable walking distances. The study also developed assumptions to distinguish “transfer’ from ‘activity’ to accurately predict the passenger destination. This study results will enable the public transport agencies to optimise the public transport routes and their schedule; which will ultimately lead to the public transport system improvements resulting in higher patronage.