The modeling of additive manufacturing (AM) processes is multidisciplinary, involving multiple physics as well as multiple time and space scales, thus requiring interdisciplinary modeling efforts. The unique manufacturing process of AM affords the tight integration of in situ measurements and computational modeling. Although AM is relatively new to the mainstream industrial landscape, it is being applied to traditional alloy chemistries. Recent research in AM titanium alloys will be presented. Particular emphasis is placed on integrated computational materials engineering software that simulates the statistical behavior of fatigue and fracture of AM materials by addressing the critical variations of novel microstructure, defects, surface roughness, and residual stress. The software accepts data from multiple sources, including data from the open literature and prior material certification programs. Thus, data available from previous certification of traditional processes (forgings, castings, and weldments) can be used to develop a baseline model. The baseline model is used to simulate the AM material by explicitly modeling the difference in the novel material microstructure, defects, surface roughness, and residual stress compared with the traditionally processed part. Electron beam melting processed Ti-6Al-4V specimens were selected for modeling and compared with test data from the open literature. The probabilistic nature of the models allows for the quantification of the tails of distributions that govern minimum properties for burst and fatigue certification. The primary benefit of this software is the decrease in the time and resources needed to certify AM structural components exposed to both monotonic and cyclic loading.