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Résumé : Green technology supply chains combine rapid demand growth with concentrated production, uneven environmental performance, and exposure to trade disruption. This article links trade network analysis, next-year bilateral trade link prediction, multi-objective portfolio optimization, and disruption stress testing across 14 importing markets and six technology and material groups from 2015 to 2024. The cleaned sample contains 15,186 supplier-year observations and USD 696.1 billion in foreign supplier trade. Concentration rose most clearly in photovoltaic equipment, lithium-ion batteries, and wind equipment. In the chronological 2022–2023 test, gradient boosting achieved ROC AUC 0.911 and a Brier score of 0.119. Logistic regression produced slightly higher AUC, while persistence retained the strongest F1. Event-specific tests show that exits and reactivations are more predictable than rare first observed entries. A historical decision comparison finds only a small and statistically uncertain advantage of calibrated gradient boosting over calibrated logistic regression, while predictive continuity information improves allocation performance relative to a specification without the probability term. Latest-year portfolios remain highly concentrated, with median HHI of 0.632 and a median top-three supplier share of 95.5%. Under balanced priorities, median HHI falls by 53.7%, and sourcing exposure to supplier-country CO2 intensity of GDP falls by 32.3%. These changes are accompanied by a 5.2% median unit value increase and a 4.8 percentage point decline in predicted next-year link activity. Joint supplier budget scenarios show that individually feasible national diversification plans can compete for the same alternatives. The framework provides a transparent basis for screening sourcing options, identifying cases that require supplier-level verification, and assessing where coordinated investment may be needed.