Decompression sickness is a complex phenomenon involving gas exchange, bubble dynamics and tissue response. Relatively simple deterministic compartmental models using empirically derived parameters have been the mainstay of the practice for preventing decompression sickness since the early 1900s. Decades of research have improved our understanding of decompression physiology, and the insights incorporated in decompression models have allowed people to dive deeper into the ocean. However, these efforts have not yet, and are unlikely in the near future, to result in a ‘universal’ deterministic model that can predict when decompression sickness will occur. Divers using current recreational dive computers need to be aware of their limitations. Probabilistic models based on the estimation of parameters using modern statistical methods from large databases of dives offer a new approach and can provide a means of standardisation of deterministic models. Future improvements in decompression practice will depend on continued improvement in understanding the kinetics and dynamics of gas exchange, bubble evolution and tissue response, and the incorporation of this knowledge in risk models whose parameters can be estimated from large databases of human and animal data.