This paper deals with two statistical models, kriging and cokriging, to replace the objective function during an optimisation process. Kriging models deal only with function values. A cokriging model is able to deal with function values and their gradients. This ability could improve the quality of the surrogate function and, as a consequence, the optimisation results. The robustness of both approaches is verified on analytical functions and on the TEAM workshop problem 25.