Understanding structure–property (SP) relationships is essential for accelerating materials innovation. Still being in the state of ongoing research and development, this is especially true for additive manufacturing (AM) in which process-induced imperfections like pores and microstructural variations significantly influence the material's properties. That is why, the present work aims at proposing an approach for accessing pore SP relationships for AM materials. For this purpose, crystal plasticity (CP) simulations on reconstructed domains based on experimental measurements are employed to allow for a microstructure-sensitive investigation. For the considered Ti–6Al–4V specimen manufactured by laser powder bed fusion, the microstructure and pore characteristics are obtained by utilizing light microscopy and X-ray computed tomography at the microscale. Employing suitable statistical analysis and reconstruction, statistical volume elements with reconstructed pore distributions are created. Using them, microscale CP simulations are performed to obtain fatigue indicating parameters. Employing a further statistical analysis, fatigue ranking parameters are derived for a comparison of different microstructures. Additionally, a comparison with the empirical Murakami's square root area concept is made. Results from first numerical studies underline the potential of the approach for understanding and improving AM materials.