In this paper, we focus on the prediction of distant events by mining sequential rules and propose the algorithm D-SR (Distant Sequential Rules). The originality of D-SR is that it mines rules with a consequent temporally distant from the antecedent by applying a minimal gapconstraintbetweenthetwoelements. D-SRcanbeintegratedintotraditionalalgorithmsas a post-processing step or during the mining process. Experiments show the efficiency of D-SR in terms of running time, scalability and in a prediction task.