A method for a driving assistance system for a vehicle, the driving assistance system including a prediction subsystem, the method comprising the following steps: accepting a set of basic environment representations, wherein each basic environment representation represents at least one first entity detected by one or more sensors in an environment of the vehicle; allocating a set of basic confidence estimates (506, 507, 510, 512, 514), wherein each basic confidence estimate of the set is associated to one of the basic environment representations, and each basic confidence estimate represents a combination of one or more detection confidences related to the associated basic environment representation; associating at least one weight to one of the basic confidence estimates, wherein the weight is related to a composite environment representation based on the set of basic environment representations and the weight indicates an effect of a detection error in the basic environment representation, to which the basic confidence estimate is associated to, on a prediction for a second detected entity, wherein multiple weights are associated in a one-to-one relation to multiple basic confidence estimates and the multiple weights are assigned relative values reflecting the relative importance of the associated basic environment representations for the prediction; calculating a weighted composite confidence estimate for the composite environment representation based on a combination of the set of basic confidence estimates with the associated at least one weight; and providing the weighted composite confidence estimate as input for an evaluation of the prediction based on the composite environment representation. accepting a set of basic environment representations, wherein each basic environment representation represents at least one first entity detected by one or more sensors in an environment of the vehicle; allocating a set of basic confidence estimates (506, 507, 510, 512, 514), wherein each basic confidence estimate of the set is associated to one of the basic environment representations, and each basic confidence estimate represents a combination of one or more detection confidences related to the associated basic environment representation; associating at least one weight to one of the basic confidence estimates, wherein the weight is related to a composite environment representation based on the set of basic environment representations and the weight indicates an effect of a detection error in the basic environment representation, to which the basic confidence estimate is associated to, on a prediction for a second detected entity, wherein multiple weights are associated in a one-to-one relation to multiple basic confidence estimates and the multiple weights are assigned relative values reflecting the relative importance of the associated basic environment representations for the prediction; calculating a weighted composite confidence estimate for the composite environment representation based on a combination of the set of basic confidence estimates with the associated at least one weight; and providing the weighted composite confidence estimate as input for an evaluation of the prediction based on the composite environment representation.