Abstract: With the continued expansion of domestic waste landfilling and the pervasive use of plastic products in China, the occurrence and migration of emerging pollutants such as di(2-ethylhexyl) phthalate (DEHP) in landfill environments have become increasingly severe, particularly at informal landfills, where the absence of engineered measures (e.g., anti-seepage systems) leads to more concealed and complex pollution risks. To address the limitations of traditional correlation-based methods in uncovering pollution-driving mechanisms, this study introduces a causal forest model to establish a causal inference framework. The model is used to systematically evaluate the causal effects and stratified heterogeneity of multiple environmental factors, including landfill characteristics, soil physicochemical properties, heavy metal contamination, and waste composition on DEHP migration. The results show that the migration process of DEHP exhibited significant nonlinear response characteristics and stratification sensitivity. The landfill age strongly promoted migration in the younger group (average treatment effect ATE=4.32), while the effect turned negative in the older group (ATE=-0.16). The inhibitory effect is strongest when the pH is in a high range (ATE=-5.66). The heavy metals Cd and Hg exhibited significant synergistic migration potential in the bottom soil layers, with ATE values as high as 49.49 and 54.80, respectively. In contrast, factors such as landfill depth and organic matter have weaker effects or threshold changes; Rubber and plastic components weakly promote migration at a moderate proportion (ATE=0.15), while ash and soil components continuously inhibit migration (ATE=-1.61--0.41). This study demonstrates the capacity of causal machine learning to identify pollution drivers in complex systems, offering a novel analytical tool for pollution control, risk zoning, and source intervention in informal landfills. It supports a paradigm shift from correlation-based attribution to mechanism-driven causal regulation, providing theoretical and methodological guidance for achieving precise and targeted solid waste pollution management.