from sklearn.linear_model import LinearRegression

def predict_yield(data):
    # Placeholder: implement actual ML model
    model = LinearRegression()
    X = data[['feature1', 'feature2', 'feature3']]  # Replace with actual feature columns
    y = data['yield']  # Replace with actual target column
    model.fit(X, y)
    predictions = model.predict(X)
    return predictions