Abstract : This work presented in this thesis constitutes a contribution to modelling and performances analysis of logistic systems by using a new stochastic Petri nets model. It addresses issues considerably concerned by industrial companies but having received very little attention by the Petri nets community in spite of an important role of Petri nets played in the study of discrete events systems. In this work, we develop a new Petri nets model called batch deterministic and stochastic Petri nets (BDSPNs) able to describe essential characteristics of logistical systems (batch behaviours, randomness, operational policies, synchronization of various flows) and more generally of discrete events systems. The model is particularly adapted for the modelling of flow evolution in discrete quantities (variable batches of different sizes) and makes it possible to describe more specific activities such as customer order processing, replenishment of stocks, production and delivery in a batch mode. With their powerful graphical and mathematical formalism, BDSPNs can capture pertinently and precisely this batch behaviour presented in various stages of these systems, which has a very important impact on their behaviour and consequently on their analysis. The work of this thesis contributes to the theory of the new model both on its analysis techniques and on its applications to logistical systems. The results obtained in this thesis make BDSPNs a powerful modelling tool for both analysis and simulation. The capability of the new model to meet real needs is shown through applications dedicated to logistical systems.