The United Nations has set an ambitious goal to achieve net zero carbon emissions by 2050. This objective requires shifting towards green and renewable energy sources instead of conventional fossil fuels to address the global energy crisis without emitting greenhouse gases. While the energy radiated by the sun is one of the most abundant sources of energy available, its efficient and optimal use remains a significant challenge. To facilitate solar-energy-based applications, estimating the amount of solar energy available is crucial. Empirical and soft computing is the most-used method to estimate solar energy. This paper aims to analyze the existing techniques used in various models for estimating and predicting the quantity and quality of solar radiation using readily available data. Additionally, the study aims to identify the most appropriate techniques for developing prediction models using available explanatory variables. To fully harness the potential of solar energy, it is necessary to limit the terrestrial loss of solar radiation by minimizing the harmful effects of anthropogenic factors that reduce the quantity and quality of solar radiation in the area. This paper provides valuable insights to identify opportunities to maximize the potential of solar energy in different locations.