Assurance of structural integrity of additively manufactured parts requires the qualification of materials, processes and machines. For the original equipment manufacturer (OEM), the speed and cost of qualification is critical for competitive advantage. During the past two decades, GE Global Research has developed and advanced the state-of-the-art of a suite of primarily Bayesian probabilistic methods and tools that have been leveraged on a wide variety of aviation, power, oil and gas and other applications for performance, cost, quality and reliability. Recently we have been applying them to additive manufacturing related qualifications. This work provides an overview of these probabilistic methods and tools and shows an application that reduces cycle time by four to five times in the development of additive alloy families.