Our focus lies on the advancement of predictive capabilities through the training of neural networks, employing the remarkable technologies of artificial intelligence and deep learning, which are being used in the dynamic realms of the real estate and financial sectors. Rent forecasting is emerging as a pivotal application scenario and presents immense potential for real estate agents, financial institutions, and property developers alike. This powerful tool provides them with the ability to make informed decisions in a rapidly changing market environment. Today, it is not uncommon to see numerous real estate websites harnessing the potential of machine learning models to offer rental price predictions, thereby simplifying the decision-making process for both tenants and landlords. The integration of machine learning models has also become increasingly prevalent among forward-thinking real estate firms and financial institutions, leading to more precise rent determinations. However, it is important to acknowledge that the endeavor of training neural networks for rent prediction remains a relatively nascent field. Continued research and experimentation are vital in our pursuit of the improvement of both the performance and accuracy of these models. As we navigate this exciting frontier, we anticipate significant advancements that will reshape the landscape of rent prediction within the real estate and financial industries.