The study deals with accurate prediction of risks of complications in microwave ablation (MWA) of non-small cell lung cancer (NSCLC) using CT-integration and clinical causal knowledge. The authors developed a system that interprets the context of the lesion based on imaging parameters such as the distance of the tumor from the pleura, the proximity of vessels and pleural adhesions, organized into causal pathways supporting risk reasoning. They retrospectively analyzed 184 cases of NSCLC treated with MWA using a 3D U-Net architecture and multitasking heads. The system achieved high segmentation accuracy (tumor 0.878, vessels 0.851, adhesions 0.863) and complication prediction with AUCs of 0.903 for pneumothorax, 0.871 for hemorrhage, and 0.847 for pleural reactions. Causal consistency was confirmed by statistically significant relationships between imaging parameters and risks of complications (eg, negative correlation between tumor-pleural distance and pneumothorax, Kendall's τ = -0.61). Geometric adjustments of the parameters in the simulations led to the expected changes in risk in 83–86% of cases. The resulting system enables an explainable and clinically meaningful risk rationale, thereby increasing the credibility and potential clinical applicability of MWA in the treatment of NSCLC.