This paper presents advanced workflows that combine 3D Xray microscopy (XRM), nanoscale tomography, and electron microscopy to generate a detailed visualization of the interior of electronic devices and assemblies to enable the study of internal components for failure analysis (FA). Newly developed techniques such as the integration of deep-learning (DL) based algorithms for 3D image reconstruction are also discussed in this article. In addition, a DL-based tool (called DeepScout) is introduced that uses high-resolution 3D XRM datasets as training data for lower-resolution, larger field-of-view datasets and scales larger-volume data using a neural network model. Ultimately, these workflows can be run independently or complementary to other multiscale correlative microscopy evaluations, e.g., electron microscopy, and will provide valuable insights into the inner workings of electronic packages and integrated circuits at multiple length scales, from macroscopic features on electronic devices (i.e., hundreds of mm) to microscopic details in electronic components (in the tens of nm). Understanding advanced electronic systems through X-ray imaging and electron microscopy, and possibly complemented with some additional correlative microscopy investigations, can speed development time, increase cost efficiency, and simplify FA and quality inspection of printed circuit boards (PCBs) and electronic devices assembled with new emerging technologies.