The vacation rental industry has grown considerably in the past few years, creating a need for optimal pricing strategies that balance supply and demand. This paper proposes an advanced predictive model using machine learning techniques, leveraging recent developments in cloud-based tools that make machine learning more accessible. The model aims to determine the best prices by considering dynamic market variables such as tourist season, expected demand, and specific accommodation features. The results demonstrate that the proposed model achieves high accuracy in price predictions, offering a valuable tool for property owners and managers to enhance their competitiveness and increase revenue.