This paper presents a hybrid partitioning method used to improve the performance of solving a Satisfiability (SAT) problem. The principle of our approach consists firstly in applying a static partitioning to decompose the search tree in finite set of disjoint sub-trees, then assign each sub-tree to one computing core. However it is not easy to choose the relevant branching variables to partition the search tree. We propose in this context to partition the search tree according to the variables that occur more frequently than others. The advantage of this method is to give a good disjoint sub-trees. However, the drawback is the imbalance load between computing cores. To overcome this drawback, we propose, as novelty, to extend the static partitioning by combining with a new dynamic partitioning that assures a good load balancing between cores. Each time a new waiting core is detected, the dynamic partitioning select automatically by using an estimation function the computing core which has the most work to do in order to partition dynamically its sub-tree in two parts. It keeps one part and gives the second part to the waiting core. Preliminary results show that a good speedup is achieved by using our hybrid method.