This research endeavors to revolutionize agricultural decision-making through the development and application of a robust Decision Support System (DSS) employing the Multi-Criteria Decision Making (MCDM) method. Recognizing the complexities inherent in crop selection, the study aims to bridge the gap between traditional manual methodologies and the need for a more comprehensive, objective, and data-driven approach. The research foundation rests on the understanding that crop selection is a multifaceted process influenced by diverse and interrelated factors. Leveraging technology and structured methodologies, the developed DSS offers a systematic and holistic evaluation of potential crops by integrating various criteria such as climate suitability, market demand, soil fertility, and sustainability metrics. The system's ability to consider multiple criteria simultaneously surpasses conventional single-factor approaches, providing stakeholders with a nuanced and comprehensive perspective. While demonstrating strengths in comprehensive evaluation and objectivity, the research also identifies areas for improvement. The dependency on data quality and quantity emerges as a limitation, urging the need for enhanced data sourcing and refinement. Additionally, further development in handling intricate trade-offs and improving user accessibility could bolster the system's applicability and acceptance within agricultural practices. The practical implications of this research reverberate across the agricultural domain.