Personalized dietary planning became the state of art method for weight loss and management. Recent efforts to compute personalized meal-plans focused on the use of machine learning and large language models. These tools achieved a good level of accuracy and could serve as a starting point if it is complemented by physician review. However, these tools suffer from different drawbacks that limit their use for personalized planning. These briefly include accurate calory computation, compliance with USDA guidelines, and do not take the culture specific components in terms of food choices, eating habits, or budget into consideration. In this paper, we introduce PMP-LLM (Personalized Meal Planner – Large Language Models) as a culturally specific AI-based system to generate safe, individualized meal plans. It is based on leveraging large language models (LLMs) combined with structured nutritional intelligence. Our system has been trained and evaluated over datasets composed of real and virtual cases. Its performance is comparable to dieticians and could cover the cultural aspects more than the general purpose LLMs tools.