In this project, our team analyzed Boston Airbnb listings to identify the key factors that influence nightly rental prices. Using a multivariable regression model, we evaluated the impact of features such as property type, number of bedrooms and bathrooms, accommodation capacity, and user reviews. We applied backward regression to refine the model and found that entire home listings and additional amenities significantly increase pricing, while high review counts may indicate more competitive pricing. This project helped inform both guests and hosts on fair pricing and strategic listing optimization.