This project aimed to develop a robust sentiment analysis model specifically designed for restaurant reviews, particularly for the House of Jollof. By applying advanced Machine Learning and Deep Learning techniques, including Recurrent Neural Networks (RNN) with Gated Recurrent Units (GRU) and Long Short-Term Memory (LSTM) layers, the model effectively predicts customer sentiments from text data. The insights derived from this analysis enable the restaurant to understand customer feedback at a granular level, driving strategic decisions for business development. Through the use of these models, the project also explored various architectures to determine the most accurate approach, resulting in significant improvements in predicting customer sentiment, which is crucial for enhancing customer satisfaction and loyalty.