In recent years, meal calorie management has played an important role in health maintenance and dieting. Particularly, interest in recording meal content and calories has increased, and various apps that support this have been provided. However, many apps that focus too much on convenience suffer from reduced accuracy or have usability issues. For example, some apps require users to manually input the type and amount of food one by one, requiring prior knowledge about food, while others automatically recognize food types from food images but have fixed calorie values regardless of quantity. Therefore, this research proposes a system called “LiDARCalorieCam” that estimates meal calorie amounts in real-time using the LiDAR sensor installed in iPhones. This system takes images of meals and obtains the three-dimensional shape of the food using depth sensors. Based on the three-dimensional shape, it estimates food volume and calculates calories based on the volume. Building on existing research, we expanded the range of supported meal categories and improved calorie estimation accuracy, achieving more reliable calorie estimation.