Increasing rates of success in liver transplantation have increased the number of cases considered. However, liver post-transplant graft dysfunction of liver transplants (TXs) is not fully understood and by applying holistic approaches we can investigate metabolic change deriving from confounding factors such as liver fat content, ischaemia time, donor age, recipient's health, etc. Twenty-six hepatic bile samples taken from liver donors and recipients were retrieved from a total of six TXs, from these one recipient underwent post-graft dysfunction. CE was employed to fingerprint bile collected at 10 min increments in the donors and in the recipients. The electropherograms of these samples were aligned and normalised using correlation optimised warping algorithms and modelled with multivariate techniques. The resulting metabolic signatures were compared; in general donors and recipients showed distinct fingerprints and clustered separately. When a partial least square discriminant analysis (PLS-DA) model was constructed between donor and recipient's samples, a recipient of a 32 year old liver with normal steatosis, and shortest cold ischaemia time showed as the observation nearest to its donor observation, denoting minimal metabolic change. This study proposes CE fingerprinting of human bile as a promising technique to help unravel the complex metabolic pathways involved during transplantation.