In ‘dynamic’ prediction of survival we make updated predictions of individuals’ survival as new longitudinal measures of health status become available. Landmarking is an attractive and flexible method for dynamic prediction. In this talk I will take the audience through a dynamic prediction analysis using data from the UK Cystic Fibrosis Registry. Challenges arise due to a large number of potential predictors, use of age as the timescale, and occurrence of intermediate events. Various modelling options are possible, and choices have to be made concerning time-varying effects and landmark-specific effects. I will outline how different model selection procedures were investigated; how models were assessed and compared using bootstrapping; and how predictions and their uncertainties can be obtained for a new individual.