In order to solve the analysis problem more efficiently and quickly, we presented a hybrid method based on LS-SVM and Bacterial Foraging Optimization (BFO) in this study. The social foraging behavior of Escherichia coli bacteria has been used to solve optimization problems. This paper proposes a hybrid approach involving Bacteria Foraging Optimization Algorithm (BFO) and LS-SVM algorithms for prediction problems. It is found that Bacteria Foraging Algorithm (BFO) is capable of improving the speed of convergence as well as the precision in the desired result. Simulation results clearly illustrate that the proposed approach is very efficient and could easily be extended for other global optimization problems. It can conclude that BFO is effective and rapid for the cluster analysis problem.