English Language Teaching (ELT) continues to encounter challenges in adapting instructional methodologies to enhance language teaching and acquisition effectively. This study is anchored in four key educational and linguistic theories—Constructivist Learning Theory, Cognitive Load Theory, Communicative Competence Theory, and Lexical Priming Theory—that collectively support the development of an integrated, taxonomy-driven model for ELT. Using qualitative in-depth content analysis of scholarly books and journals, supplemented by interviews and classroom observations, the research examines how taxonomy-driven instruction enhances lesson planning, assessment standardization, and multilingual adaptability. A sample of 20 participants (P-1 to P-20) provided empirical insights into cognitive engagement, lexical retention, and fluency-building through structured learning sequences. Findings reveal that taxonomy-aligned instruction strengthens comprehension, supports assessment standardization, and facilitates multilingual adaptability, while AI-assisted learning tools enhance adaptive pedagogical strategies in a blended learning context. To address these persistent challenges, this study proposes a taxonomy-driven model, offering educators a structured and adaptable framework for more effective and inclusive language instruction.