This research presents a novel approach to English language teaching by developing an intelligent framework that integrates fuzzy logic systems with green pedagogy principles. The study addresses the growing need for educational methodologies that simultaneously enhance language proficiency and environmental consciousness. Through the implementation of a Mamdani-type fuzzy inference system, the framework processes multiple input variables—environmental awareness levels, language proficiency, and green vocabulary knowledge—to generate optimized teaching strategies tailored to diverse learner profiles. The system employs triangular membership functions and a comprehensive rule base of fifteen conditional statements to model the complex relationships between language acquisition and environmental education. Empirical validation demonstrates significant improvements in both linguistic competence and ecological literacy among participants compared to traditional teaching methods. This intelligent framework provides educators with a systematic tool for decision-making in green language pedagogy while accommodating the inherent uncertainty in educational processes. The findings contribute to the emerging field of computational intelligence in sustainability education and offer practical implications for curriculum designers and language instructors seeking to incorporate environmental dimensions into language teaching practices.