The complexity of local and dynamic thermal transformations in additive manufacturing (AM) processes makes it difficult to track in situ thermomechanical changes at different length scales within a part using experimental process monitoring equipment. In addition, in situ process monitoring is limited to providing information only at the exposed surface of a layer being built. As a result, an understanding of the bulk microstructural transformations and the resulting behavior of a part requires rigorous postprocess microscopy and mechanical testing. In order to circumvent the limited feedback obtained from in situ experiments and to better understand material response, a novel 3D dislocation density based thermomechanical finite element framework has been developed. This framework solves for the in situ response much faster than currently used state-of-the-art modeling software since it has been specifically designed for AM platforms. This modeling infrastructure can predict the anisotropic performance of AM-produced components before they are built, can serve as a method to enable in situ closed-loop process control and as a method to predict residual stress and distortion in parts and thus enable support structure optimization. This manuscript provides an overview of these software modules which together form a robust and reliable AM software suite to address future needs for machine development, material development, and geometric optimization.