The purpose of this research was to develop an Android AI-based nutrition-driven Android app that is adapted to the needs of pregnant women. It can offer individualized food suggestions based on each person’s unique dietary limitations and nutritional requirements. To achieve this, the researchers carried out an advanced background investigation to obtain a full grasp of the methods and strategies already in use for creating nutrition apps for pregnant women. Based on this understanding, an advanced AI algorithm was developed that analyzes user data using machine learning techniques and gives consumers personalized nutritional suggestions. A performance analysis was carried out to assess the effectiveness of algorithms that have been in the development of the Prototype. The evaluation was through relevant metrics. The performance analysis has shown that the proposed prototype might perform better than current methods in providing users with personalized nutrition recommendations if it integrates the Logistic Regression Classifier algorithm with Deep Learning Regression. Nevertheless, in the future, the performance of the proposed algorithms involved in the developed prototype could be compared with the other algorithms involved in the mobile apps documented in scientific literature. The importance of personalized nutrition counseling based on dietary limitations and unique requirements is emphasized in this study, along with the potential benefits of AI-powered nutrition apps for enhancing the health of expectant mothers and their developing fetuses.