Currently, fatigue remains the main cause of failure in mechanical components during service. Furthermore, the significant statistical dispersion observed in results from experimental campaigns highlights the critical need for precise material characterization to determine fatigue behaviour. Numerous standards exist to standardize these experimental characterization tasks, such as DIN 50100, ASTM E466-15, or ISO 1099. These standards, while recognizing the importance of mini-mizing surface integrity defects because of their significant impact on fatigue life, do not provide specific recommendations on the machining process, nor do they address the impact of these varia-bles on ultimate fatigue life. Therefore, investigating optimal manufacturing conditions and their effects on roughness and residual stresses is crucial for acquiring reliable experimental data on fa-tigue life characterization. In the present study, a four-step methodology is proposed to assess the impact of surface integrity on fatigue life. Firstly, a predictive model is developed to establish the relation between machining conditions and surface integrity parameters. Secondly, the aforemen-tioned model is optimized to define different scenarios combining varying levels of both roughness and residual stresses. Based on this optimization, specimens of 42CrMo4+QT steel were machined accordingly to the previously selected cutting scenarios and subjected to fatigue loading (R = 0.1) until failure. The outcomes of each scenario were then critically evaluated, facilitating a compre-hensive comparison and discussion of how residual stress and roughness influence ultimate fatigue life.