Transformer engineering has a central role in guaranteeing the stability, dependability, and effectiveness of the present-day power frameworks. This chapter presents a detailed overview of transformer infrastructure, starting firstly, by commenting on the fundamental role of these instruments in electricity networks, and secondly, the different types of these instruments used at different voltage levels and in different applications. Multi-function devices and inelastic deformations under various constructive conditions are described; key performance parameters and transformer design scope are given, covering voltage regulation, efficiency, impedance, and losses determined under load and no-load conditions. The structure of transformers is broken up into its main parts (core materials, winding arrangements, and insulating systems containing oil types and their thermal properties). The chapter also offers to explore the cooling techniques of great importance to thermal management and provides the strategy of transformer design optimization. It is emphasized that manufacturing and operational costs and performance standards can be minimized. In addition, recent developments in artificial intelligence, such as artificial neural networks (ANNs), are introduced as powerful tools for optimization of transformer design. Using these techniques can enable increasing accuracy of modeling, increased design iteration speediness, and better predictions of performance. Overall, the chapter brings the engineering and computer intelligence together, building a progressive road to affordable, efficient, and intelligent transformer generation.