 This paper proposes an ensemble federated learning-based approach for multi-order lung cancer classification that combines multiple machine learning models trained on different datasets, improves accuracy and generalization, and ensures data privacy and security using distributed data. The results demonstrate an accuracy of 89.63% with lung cancer classification on a Kaggle cancer dataset. This article was authored by Oma Mahazwer and Shabash Chandra Bose, Rajan John, Bhusha Virasamy and Bhazagu, and others.