Climate change manifests unequivocally and multidimensionally through rising global temperatures, increasingly unpredictable shifts in rainfall patterns, and the escalating frequency and intensity of extreme climate events. These phenomena significantly disrupt agricultural production systems' stability, particularly in rural areas serving as national food buffers but possessing limited adaptive capacity. This study aims to construct and test a comprehensive multivariate model to predict the simultaneous impact of environmental variables (temperature, rainfall, extreme events) on rural socio-economic conditions, focusing specifically on agricultural productivity and farmers' adaptation strategy decisions. Employing a quantitative explanatory research design with a Structural Equation Modeling - Partial Least Squares (SEM-PLS) approach, this study involves rice farmers in Purwakarta Regency selected via purposive sampling. Empirical analysis results indicate that the constructed model possesses very strong explanatory power, with determination coefficient values (R2) exceeding 96% for both dependent variables. Key findings reveal that extreme climate events (such as flash floods and prolonged droughts) have the most destructive negative impact on productivity and serve as the primary driver for farmers' adaptation strategies. A crucial paradoxical finding emerged where current adaptation strategies proved insignificant in improving productivity, indicating that farmers' adaptations remain reactive (coping mechanisms) rather than reaching an effective transformative stage.