We present a new bundle algorithm for minimizing convex not necessarily smooth functions. The novelty of our approach is based on a bundle modification strategy that we apply whenever the stability center is updated and which is aimed at substituting the points of the bundle by new points characterized by possibly better values of the objective function. Convergence of the algorithm is proved and numerical results are presented.