To predict the need for vasopressor therapy, arterial blood pressure and heart rate are taken as inputs to a fuzzy-logic based algorithm that generates a 'vasopressor advisability index'. We evaluated the algorithm against patient records from a large intensive care database. The algorithm achieved a sensitivity of 69.7% and a specificity of 84.2% on a test set that was independent of the training set used.