This study investigates the effectiveness of REDD+ projects in reducing carbon emissions and their socioeconomic impacts on local communities, focusing on the Maísa REDD+ project in Pará, Brazil. Using a causal inference approach, the research applies remote sensing data to estimate avoided deforestation while integrating co-benefit assessments into conservation evaluations amid concerns over REDD+ credit integrity. The study examines whether REDD+ projects reduce deforestation but may be over-credited, and how their socioeconomic impacts vary across communities. Employing a synthetic control methodology to address spatial autocorrelation and unobserved confounders, the research combines field interviews, remote sensing analysis, and semi-structured stakeholder interviews to improve conservation impact assessments and strengthen REDD+ project credibility.