The study utilizes explainable artificial intelligence (XAI) combined with machine learning to assess how inter‑annual weather variability influences oilseed sunflower yields across the United States from 1976 to 2022. Key climate predictors, especially summer maximum temperature and total precipitation, were identified, and predictive models were projected under various Shared Socioeconomic Pathways to 2080, revealing region‑specific yield declines.