Constraint Optimization problems are commonly solved using a Branch and Bound algorithm enhanced by consistency maintenance procedures (Wallace and Freuder 1993; Larrosa and Meseguer 1996; Larrosa et al. 1999; Larrosa and Schiex 2003; 2004). All these algorithms traverse the search space in a chronological order and gain their efficiency from the quality of the consistency maintenance procedure. The present study introduces Conflict-directed Backjumping (CBJ) for Branch and Bound algorithms. The proposed algorithm maintains Conflict Sets which include only assignments whose replacement can lead to a better solution. The algorithm backtracks according to these sets. CBJ can be added to all classes of the Branch and Bound algorithm. In particular to versions of Branch & Bound that use advanced maintenance procedures of soft local consistency levels, NC*, AC* and FDAC (Larrosa and Schiex 2003; 2004). The experimental evaluation of B&B_CBJ on random Max-CSPs shows that the performance of all algorithms is improved both in the number of assignments and in the time for completion.