The majority of Thai people often hold beliefs regarding fate and auspiciousness, such as looking at Feng Shui, enhancing luck through various methods, including planting auspicious trees with a wide variety of species. Some species may closely resemble each other, leading to confusion when selecting auspicious trees based on individual beliefs.  Therefore, this research aims to develop and evaluate the effectiveness of a deep learning model for classifying 10 types of small-sized auspicious trees suitable for planting in limited spaces according to current lifestyle patterns, using Convolutional Neural Network algorithms. Subsequently, this model will be applied to develop a mobile application for species classification and providing information on small-sized auspicious trees using image recognition techniques. Finally, the satisfaction with the developed mobile application will be assessed. The research findings indicate that the evaluation of the performance of the deep learning model for classifying small-sized auspicious trees yields an average accuracy of 92%. In developing the mobile application for classifying species and providing information on auspicious trees, the researchers utilized Visual Studio Code, Flutter Framework, and Dart programming language, along with the Firebase database management system. The evaluation of user satisfaction with the mobile application usage among a sample group of 50 individuals interested in purchasing auspicious trees revealed that it was rated as good or very good in every aspect. The overall satisfaction with the application usage averaged 4.45. Therefore, it can be concluded that the developed mobile application can serve as another channel to support individuals interested in purchasing small auspicious trees, enabling them to classify the types of auspicious trees and access basic information about the trees they are interested in.