Understanding the relationship between energy use and well-being is crucial for designing holistic energy policy. The latter has to both effectively mitigate climate change driven by current fossil-based energy systems as well as promote human development, which requires energy. While a significant body of research investigates this relationship, study designs differ significantly, so findings cannot be easily generalized. This machine learning-aided review provides an overview of the current state of the literature examining this relationship. We highlight and discuss methodological differences between the studies, including their perspective (top-down or bottom-up), spatial scope, and the respective energy and well-being indicators used. The review reveals that most research takes a top-down perspective, analyzing country-level data across multiple countries. These studies typically find a positive relationship between energy use and well-being, and most confirm the existence of a saturation effect. We reveal that countries in the Global South are underrepresented in current studies. Bottom-up studies focus on specific countries or country groups using household-level data, yielding more nuanced findings that can be further disaggregated by consumption domain. We find that energy and well-being indicators differ substantially across studies, yet the implications of this choice are not always sufficiently discussed. The review shows and discusses the current shift from production- to consumption-based energy indicators.