A machine learning project that predicts whether an order will be delayed or delivered on time using historical order data. The system trains a Random Forest classifier with proper data preprocessing and saves the trained model for future use.

This project analyzes order delivery data to identify patterns that lead to delivery delays. It uses structured preprocessing pipelines for numerical and categorical features and builds a reliable classification model to predict delays.

The trained model is saved and can be reused in production or integrated into other applications.

• Predicts delivery delay (Delayed / On-time)
• Automatic data preprocessing
• Handles missing values
• Feature scaling and encoding
• Random Forest classification model
• Model evaluation with accuracy and classification report
• Saves trained model as a reusable file

• Programming Language: Python
• Data Processing: Pandas, NumPy
• Machine Learning: Scikit-learn
• Model Persistence: Joblib