This paper embeds machine learning predictions into an n8n-orchestrated Agile workflow, using XGBoost for assignee recommendation and Random Forest with quantile regression for deadline prediction. The assignee model reached 95.15% Top-3 accuracy, and the deadline intervals achieved 88.09% coverage with a median MAE of 6.16 days.