NTpred is a robust and precise machine learning framework capable of performing computational identification of Tyrosine nitration sites in protein sequences. It employs gap-based Amino Acid Compositional encoders to transform protein sequences into statistical feature space, and utilizes a Hybrid Ensemble Classifier that comprises of Gradient Boosted Trees and Logistic Regression. "Standrad" training mode can be used to perform Independent test setting. A trained model is deployed using the user provided training data. The trained model can be used for Prediction by the user.