In this paper, we study how exploiting multiple differential characteristics with a common initial difference and different output differences improves the complexity of differential cryptanalysis attack. We call such an approach Multiple Differential Cryptanalysis. We describe such an attack rigorously by studying the probability distribution of multiple differential characteristics and giving an attack algorithm based on LLR statistic. We also present a statistical analysis on the attack complexity based on LLR probabilistic technique. Our analysis shows that the data complexity of the proposed attack decreases as the number of characteristics increases. We do an experiment with the described method to show its improvements through cryptanalyzing a reduced round PRESENT block cipher with 5 rounds.