This paper presents a tuning method of Smith predictor controller based on the difference between model parameters and real ones, in contrast with standard methods that consider an exact model match. For first order process models, without and with integrator and parametric uncertainties, was demonstrated that proposed tuning solution ensures the robustness of stability and performances.