A technique to predict the variability of the Paris regime fatigue crack growth rates in ductile materials based on bulk property (yield strength, hardening modulus, and fracture toughness) variation is presented. The prediction, based on the plastic dissipation in the reversed plastic zone ahead of the crack tip, is carried out for Ti-6Al-4V. The empirical distributions of the bulk properties of Ti-6Al-4V are characterized and directly used in the probabilistic assessment of the fatigue crack growth rate. Since computing the plastic dissipation is a computationally intensive procedure, a novel sampling scheme based on confidence interval minimization was used to generate the empirical distribution of fatigue crack growth rate. This technique also predicts correlation between fatigue crack growth rate and fracture toughness, which may be useful in probabilistic design of turbines.