The purpose of this study is to design a model for renewable energy development based on sustainable marketing using a Fuzzy Cognitive Map (FCM) approach. In terms of purpose, this is an applied study, and regarding its nature, it follows a mixed-methods (qualitative–quantitative) design. The statistical population in the qualitative phase comprised 21 experts in biosystems, renewable energy, and marketing professors, while the quantitative phase included 14 experts, all selected through non-probability snowball sampling. Data collection was conducted using semi-structured interviews. For data analysis, Grounded Theory and the Fuzzy Delphi Method were employed. In the quantitative phase, 40 out of 41 components were confirmed; subsequently, through expert participation and focus group discussions, relational strength matrices were calculated for the three categories of factors, strategies, and outcomes, leading to the construction of the Fuzzy Cognitive Map. The findings revealed that among the causal factors, ‘data-driven and informational policy-making’ was the most influential factor, with a centrality of 5.90 and an out-degree (influence) of 2.98, while ‘structural transformation in the energy system’ was the most receptive factor, with an in-degree (receptivity) of 3.03. Among the strategies, ‘improving regional and local policies’ emerged as the most critical strategy with a centrality of 4.49, and within the outcomes, ‘regional and local transformation’ held the highest significance with a centrality of 4.32. Furthermore, quadrant analysis indicated that ambidextrous/two-way components—such as data-driven policy-making and improving regional policies—fall into Quadrant I (high influence and high receptivity), whereas components such as cultural-social barriers and human-knowledge challenges are situated in Quadrant II (influential/driving factors).