Despite the advances in imaging modalities and surgical techniques, the management of adults with congenital heart disease (ACHD) over the years has remained largely empirical rather than evidence-based. Animal models have been difficult to develop and very costly, while clinical trials are difficult to design and perform in ACHD, leaving gaps in our understanding of the pathophysiology and treatment of congenital heart disease. Disease modelling, both hypothetical and patient-specific, provides an alternative solution to many of these problems. Advances in cardiovascular imaging and diagnostics have led to the easy acquisition of large quantities of structural and functional information, which cannot be handled "intuitively". Computational modelling introduces mathematical rigour in the analysis and utilisation of these data by quantitative simulation and testing of clinically relevant hypotheses through experimentally validated models. Close multidisciplinary collaboration between bioengineers and clinicians is essential for transforming data and images derived from models of disease into clinically useful information.