Titanium alloys are employed in many advanced engineering applications due to their exceptional properties, i.e., a high strength-to-weight ratio, corrosion resistance, and high temperature strength. The performance of titanium alloys is known to be strongly affected by its inherent microstructure, which forms as a result of its thermo-mechanical processing. These microstructures produce compromise relationships between beneficial and detrimental effects on the alloy's performance. To study these structure-property relationships, two distinct crystal plasticity algorithms have been calibrated to data acquired from cyclic deformation experiments performed on three different Ti microstructures: (1) Ti-6Al-4V beta-annealed , (2) Ti-18 solution-treated, age-hardened (STA), and (3) Ti-18 beta-annealed, slow-cooled, age-hardened (BASCA). The calibrated models have been utilized to simulate fatigue loading of variant microstructures to investigate the influence of mean grain size, crystallographic texture, and phase volume fraction. The driving force for fatigue crack nucleation and propagation is quantified through the calculation of relevant fatigue indicator parameters (FIPs) and radial correlation functions are employed to study the correlation between favorably oriented slip systems and the extreme value FIP locations. The computed results are utilized to observe fatigue performance trends associated with changes to key microstructural attributes.