input: Write a python function to perform linear regression using scikit-learn and make predictions.
  assert np.isclose(predict_value([1,2,3,4,5], [3,5,7,9,13], 7), 15.4)
  assert np.isclose(predict_value([2,3,4,5,6], [4,6,8,10,12], 8), 16.0)
  assert np.isclose(predict_value([1,2,3,4,5,6], [2,4,6,8,10,14], 7), 13.0)
output: def predict_value(X, y, new_value):
      from sklearn.linear_model import LinearRegression
      import numpy as np
      
      # Convert lists to numpy arrays and reshape for sklearn
      X = np.array(X).reshape(-1, 1)
      y = np.array(y)
      
      # Create and train the model
      model = LinearRegression()
      model.fit(X, y)
      
      # Make prediction
      prediction = model.predict(np.array([[new_value]]))
      
      return prediction[0]