In recent years, experimental tests investigating properties of materials in gigacycle regime have suggested modifications to well-known statistical fatigue life models. Classical fatigue life models based on a single failure mode and by the presence of the fatigue limit, have been integrated by models that can take into account the occurrence of two failure modes (duplex S-N curve).Duplex S-N models involve a number of unknown parameters that must be statistically estimated from experimental data. The present paper proposes a simplified and automated procedure for statistical parameter estimation. The procedure is applied to experimental datasets taken from the literature. Parameter estimation is carried out by applying the Maximum Likelihood Principle and by taking into account the possible presence of runout specimens with unequal number of cycles. The application of the procedure permits to estimate different key material parameters (e.g., the characteristic parameters of transition stress and fatigue limit), as well as to statistically predict the failure mode of each tested specimen.