Asphalt binders play a critical role in the overall fatigue life of asphalt concrete because asphalt provides cohesion to the mixture by holding the aggregates together. Thus, it is imperative to characterize the resistance to fatigue damage offered by different binders. Researchers have suggested several parameters such as G*sinδ, Np20, elastic recovery, surface free energy to predict the fatigue resistance of binders. However, the ability of these parameters in capturing the fatigue behaviour of asphalt mixtures needs to be compared. In this study, several existing binder fatigue parameters were evaluated in terms of their correlation with asphalt mixture fatigue life. Existing data of fatigue life from four-point beam tests that were obtained for mixtures prepared with ten different binders were utilized for this purpose. The corresponding binders were subjected to various tests to obtain many of the binder fatigue characterization parameters. The parameters include the work of cohesion and work of adhesion from surface free energy measurements, the parameter Nf from Linear Amplitude Sweep (LAS) tests, and G*sinδ, G*cosδ, sinδ, and tanδ from oscillatory tests. The necessity for a combination of more than one parameter to accurately predict fatigue life was also explored. Blue granite aggregate and ten different binders were used in the study, including two unmodified and eight modified binders. Work of cohesion and work of adhesion were obtained from surface free energy measurements using a contact angle meter. Linear Amplitude Sweep (LAS) test and frequency sweep test was conducted in a dynamic shear rheometer. The rheological properties of the binder, such as complex shear modulus (G*) and phase angle (δ), were obtained from the frequency sweep tests. The parameters were then compared with the fatigue life obtained from tests on the corresponding asphalt mixtures. It was found that tanδ had the highest correlation with the fatigue life of mixtures. Also, tanδ, when combined with work of adhesion, resulted in the best possible prediction of fatigue life of mixtures. From this, we can conclude that fracture and viscoelastic properties are both vital in ranking binders based on their resistance to fatigue.