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Multi-Criteria Decision-Making (MCDM) is widely recognized as an effective approach for identifying optimal solar energy sites. However, a common challenge with MCDM lies in the ambiguity surrounding the criteria framework and the importance assigned to each criterion, often based on expert judgment. This reliance on human judgment can introduce vagueness and bias. To address these limitations, researchers have begun deriving the order of importance for criteria by analyzing influential, high-impact journals. By quantifying the frequency of criteria mentioned in these journals, this method aims to reduce the influence of subjectivity and bias. Therefore, this review paper critically examines the influential criteria for identifying optimal solar energy sites, based on high-impact journals published between 2020 and 2023. It analyzes the relative importance of sub-criteria using citation frequency to address gaps in the current state of the art. From the five main criteria (climatic, technical, accessibility, environmental, and social), a comprehensive framework comprising 47 sub-criteria is developed. The paper also assesses 17 prominent MCDM algorithms, highlighting their strengths and limitations in the context of solar energy site selection. Additionally, a comparative analysis of five prominent MCDM methods is conducted to evaluate geographic divisions in Sarawak based on specific criteria. Spearman’s rank correlation is employed to measure the agreement among these MCDM methods. The results reveal that normalization methods or preference functions within each MCDM method achieved a consistency level greater than 70 %. However, the low average correlation value of 0.1105 (out of a maximum of 1) among different MCDM methods indicates significant variations in rankings. This underscores the importance of carefully selecting the most appropriate MCDM method based on the specific decision context and the desired level of consistency.