Abstract: Downy mildew caused by Bremia lactucae is a major threat to lettuce production. Infected leaves show chlorotic spots and under humid conditions sporulating mycelium, making the entire head of lettuce unmarketable. Currently, growers rely largely on fungicides applications according to a fixed schedule to control this disease. In an effort to reduce the number of fungicide applications a decision support system (DSS) was developed. This DSS is driven by the greenhouse climate data and input of information from previous fungicide applications. In short, the DSS determines whether climate conditions are favorable for infection and/or sporulation by B. lactucae at any given moment and if the lettuce crop is still protected by a previous preventive treatment. If not, a warning is send to the user with the suggestion of a suitable fungicide, based on the history of prior applications and empirically determined data on fungicide efficacy. The aim of the current study was to validate the DSS by comparing the incidence of B. lactucae infections on lettuce heads treated according to the conventional fixed spray schedule and according to the warnings of the DSS. Our data suggest that a comparable number of fungicide applications is required when following the fixed schedule and the DSS. However, when following the DSS efficacy of the applications could be increased. Although further optimization of the DSS is recommended, it is expected to become a valuable instrument in pursuing a more rational use of fungicides.