This study aims to analyze the determinants of corn farmers' income in Stabat District, Langkat Regency. The main issue addressed in this research is the fluctuation of farmers' income influenced by various internal and external factors. The variables examined include land area, farming experience, informal education, selling price, productivity, technology adoption, and access to capital. This study employs a quantitative approach with a sample of 195 corn farmers selected using a structured sampling technique. Primary data were collected through questionnaires and direct interviews with respondents, while secondary data were obtained from relevant institutions and literature. Data analysis techniques used are Confirmatory Factor Analysis (CFA) to identify dominant factors and Multiple Linear Regression to examine both partial and simultaneous effects of the variables. Prior to analysis, classical assumption tests, including normality, multicollinearity, and heteroscedasticity tests, were conducted to ensure the validity of the regression model. The results show that simultaneously all independent variables have a significant effect on farmers' income. Partially, land area, informal education, and selling price have a positive and significant effect on income. The analysis also reveals that selling price is the most dominant variable in determining farmers' income. In contrast, technology adoption and access to capital do not show significant effects in the model. These findings imply the importance of maintaining price stability, improving market access, and strengthening farmers' capacity through extension services and training programs to enhance productivity and welfare. Furthermore, policy support from the government is needed to create a more sustainable agricultural system and reduce income volatility among corn farmers in the study area. In addition, improving infrastructure, strengthening farmer institutions, and enhancing access to market information are essential strategies to support income growth and long-term agricultural sustainability.