<![CDATA[The growth of financial technology has strengthened the role of digital payments indriving the digital economy and influencing investment decision-making. This developmentcreates both opportunities and challenges for investors in evaluating digital payment investments.Multi-Criteria Decision Analysis (MCDA) supports structured evaluation across multiple criteria,while Machine Learning (ML) enhances predictive capabilities using historical and market data.However, studies integrating MCDA and ML remain limited and unsystematic. This studyconducts a systematic literature review (SLR) based on the PRISMA framework, analyzingpublications from 2019 to 2024 related to the application of MCDA and ML in digital paymentinvestment and decision-making. The results indicate an increasing research trend, with commonlyapplied MCDA methods such as AHP, TOPSIS, and PROMETHEE, and ML algorithms includingSupport Vector Machine and Gradient Boosting. This review identifies research gaps and providesdirections for future studies and practical investment strategies in the digital payment sector. Keywords: Digital Payment; Investment; MCDA; Machine Learning; Systematic Literature Review.]]>
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