My Machine Learning model doesn't work in Heroku but works perfectly on my local machine

I have created an ML model for House price prediction using Flask. It is a Web Application. When I run it locally it works perfectly fine but after deploying it in Heroku the ML model doesn't work at all perhaps the web application runs perfectly.

Here is the link of my Web App: https://ml-housepriceprediction.herokuapp.com/

I have created a Flask server for my web app as well as ML model in a single file named as "app.py"

app.py

    from flask import Flask, request, jsonify
    from website import create_app
    import util
    import util_2
    import util_3

    app =  create_app()


    # bangalore
    @app.route('/get_location_names', methods=['GET'])
    def get_location_names():
        response = jsonify({
            'locations': util.get_location_names()
        })
        response.headers.add('Access-Control-Allow-Origin', '*')

        return response

    @app.route('/predict_home_price', methods=['POST'])
    def predict_home_price():
        total_sqft = float(request.form['total_sqft'])
        location = request.form['location']
        bhk = int(request.form['bhk'])
        bath = int(request.form['bath'])

        response = jsonify({
            'estimated_price': util.get_estimated_price(location, total_sqft, bhk, bath)
        })

        response.headers.add('Access-Control-Allow-Origin', '*')

        return response

    #mumbai
    @app.route('/get_location_names_m', methods=['GET'])
    def get_location_names_m():
        response = jsonify({
            'locations': util_2.get_location_names()
        })
        response.headers.add('Access-Control-Allow-Origin', '*')

        return response

    @app.route('/predict_home_price_m', methods=['POST'])
    def predict_home_price_m():
        total_sqft = float(request.form['total_sqft'])
        location = request.form['location']
        bhk = int(request.form['bhk'])
        bath = int(request.form['bath'])

        response = jsonify({
            'estimated_price': util_2.get_estimated_price(location, total_sqft, bhk, bath)
        })

        response.headers.add('Access-Control-Allow-Origin', '*')

        return response

    #delhi
    @app.route('/get_location_names_d', methods=['GET'])
    def get_location_names_d():
        response = jsonify({
            'locations': util_3.get_location_names()
        })
        response.headers.add('Access-Control-Allow-Origin', '*')

        return response

    @app.route('/predict_home_price_d', methods=['POST'])
    def predict_home_price_d():
        total_sqft = float(request.form['total_sqft'])
        location = request.form['location']
        bhk = int(request.form['bhk'])
        bath = int(request.form['bath'])

        response = jsonify({
            'estimated_price': util_3.get_estimated_price(location, total_sqft, bhk, bath)
        })

        response.headers.add('Access-Control-Allow-Origin', '*')

        return response

    if __name__ == "__main__":
        print("Starting Python Flask Server For Home Price Prediction...")
        util.load_saved_artifacts()
        util_2.load_saved_artifacts()
        util_3.load_saved_artifacts()
        app.run()

Procfile

web: gunicorn app:app

requirements.txt

    asgiref==3.3.1
    astroid==2.5
    autopep8==1.5.6
    beautifulsoup4==4.9.3
    bs4==0.0.1
    certifi==2020.12.5
    chardet==4.0.0
    click==7.1.2
    colorama==0.4.4
    Django==3.0.4
    Flask==1.0.2
    Flask-Login==0.5.0
    Flask-SQLAlchemy==2.5.1
    greenlet==1.0.0
    gunicorn==20.1.0
    html5lib==1.1
    idna==2.10
    isort==5.7.0
    itsdangerous==1.1.0
    Jinja2==2.11.3
    joblib==1.0.1
    lazy-object-proxy==1.5.2
    MarkupSafe==1.1.1
    mccabe==0.6.1
    MouseInfo==0.1.3
    numpy==1.20.1
    Pillow==8.2.0
    PyAutoGUI==0.9.52
    pycodestyle==2.7.0
    PyGetWindow==0.0.9
    pylint==2.7.0
    PyMsgBox==1.0.9
    pyperclip==1.8.2
    PyRect==0.1.4
    PyScreeze==0.1.27
    PyTweening==1.0.3
    pytz==2021.1
    pywhatkit==4.7
    requests==2.25.1
    scikit-learn==0.24.2
    scipy==1.6.2
    six==1.15.0
    sklearn==0.0
    soupsieve==2.2.1
    SQLAlchemy==1.4.12
    sqlparse==0.4.1
    threadpoolctl==2.1.0
    toml==0.10.2
    urllib3==1.26.4
    webencodings==0.5.1
    Werkzeug==1.0.1
    wikipedia==1.4.0
    wrapt==1.12.1