This paper investigates the effectiveness of e-learning platforms using the Weighted Product (WP) method integrated into a Decision Support System (DSS) framework. The WP method quantitatively evaluates platforms based on multiple weighted criteria, including learner satisfaction, engagement levels, content relevance, educational outcomes, and technical reliability. Our analysis, focusing on three distinct platforms, reveals Platform A as the most effective, with Platform B and C following, based on both aggregated and normalized effectiveness scores. While the WP method ensures a comprehensive and adaptable evaluation, facilitating objective platform comparisons, it faces challenges such as complexity in implementation, sensitivity to subjective weight assignments, and a predominant focus on quantitative metrics. Future research is recommended to incorporate qualitative assessments, develop automated weight adjustment techniques, and enhance the DSS user interface for broader accessibility. These advancements could refine the evaluation process, making it more robust and user-friendly, thereby better supporting stakeholders in making informed decisions about e-learning strategies.