Cardiomyopathy syndrome (CMS) has been an economically important disease in Norwegian aquaculture since the 1990s. In this study, data on monthly production characteristics and case registrations were combined in a cohort study and supplemented with a questionnaire-based case-control survey on management factors in order to identify risk factors for CMS. The cohort study included cases and controls from 2005 to 2012. From this dataset differences between all cases and controls were analyzed by a mixed effect multivariate logistic regression. From this we found that the probability of CMS increased with increasing time in the sea, infection pressure, and cohort size, and that cohorts which had previously been diagnosed with heart and skeletal muscle inflammation or which were in farms with a history of CMS in previous cohorts had double the odds of developing CMS. The model was then used to calculate the predicted value for each cohort from which additional data were obtained via the questionnaire-based survey and used as offset for calculating the probability of CMS in a semi-univariate analysis of additional risk factors. Finally, the model was used to calculate the probability of developing CMS in 100 different scenarios in which the cohorts were subject to increasingly worse conditions with regards to the risk factors from the dataset. We believe that this exercise is a good way of communicating the findings to farmers, so they can make informed decisions when trying to avoid CMS in their fish cohorts.