🚀 Loan Prediction Web App

A Flask-based web application for predicting loan approval using a machine learning model.

📸 Demo

👉 👉

📂 Project Structure

├── loan_prediction_api │ ├── templates │ │ ├── index.html │ │ ├── predict.html │ ├── static │ ├── app.py │ ├── model.pkl │ └── requirements.txt ├── README.md └── .gitignore

🛠️ Technologies Used

• Python
• Flask
• Scikit-learn
• HTML + CSS
• Bootstrap (Optional)

🚀 How to Run Locally

1. Clone the repository

git clone https://github.com/allwin10/loan-prediction-web-app.git
cd loan_prediction_api

2. Create a virtual environment

python -m venv venv
source venv/bin/activate   # For MacOS/Linux
venv\Scripts\activate      # For Windows

3. Install dependencies

pip install -r requirements.txt

4. Run the app

python app.py

5. Open your browser and go to:
   👉 http://127.0.0.1:5000

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📊 Model Details

• Model: RandomForestClassifier
• Input Features: 14
• Prediction: Approved or Rejected

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🌟 Features

✅ Predicts loan approval based on user inputs
✅ Clean and responsive UI
✅ One-hot encoding for categorical data
✅ Flask-based backend

🤝 Contributing

1. Fork the repository
2. Create a new branch (git checkout -b feature/your-feature)
3. Commit your changes (git commit -m 'Add new feature')
4. Push to the branch (git push origin feature/your-feature)
5. Open a Pull Request