Fake news can mislead public opinion, weaken social order, limit the legitimacy of government, and lead to a serious threat to social stability. Therefore, the early detection of fake news from the online platform is extremely important. Most of the previous literature has focused on finding fake news from resource-rich languages like English, Hindi, and Spanish. The current work utilizes the dataset of Urdu language for fake news detection. Two different models have been proposed in the paper. The first one is an ensemble-based technique and the second one is a multi-layer dense neural network. The multi-layer dense neural network-based approach performed better with character n-gram TF-IDF features to achieve a macro 𝐹 1 -score of 0.8101.