In manufacturing, several factories consume a significant amount of energy for production and logistics processes. For these factories, the total cost of production can increase considerably as the energy cost increases. Such an increase adds to the final cost of the products reaching the consumers. As a result, energy efficiency has been considered an important decision-making aspect besides productivity, quality, cost, and flexibility in manufacturing. However, making good decisions to improve energy efficiency in manufacturing is a complex and difficult undertaking. These decisions require tradeoffs among many factors affecting these processes to reach good outcomes. This makes realizing different methods that utilize innovative technologies and help in decision making related to energy efficiency in manufacturing tremendously important. Unfortunately, there are only limited methods and tools developed for decision making support for energy efficiency of manufacturing processes. In this paper, a framework for employing digital twins for energy-efficient manufacturing is developed. One part of this framework, different advanced digital twins-based tools for energy-efficient manufacturing can be used. This paper discusses these potential advanced tools and their advantages in improving the decisions made for energy-efficient manufacturing. These advanced tools provide various approaches to evaluate and make decisions related to energy-efficiency in manufacturing.