In today’s fast-paced and modernized world, the connection between humanity and nature has significantly dwindled. As a result, the vast reservoir of knowledge present in nature, especially pertaining to medicinal plants, is gradually being overlooked. Our ancestors relied on these natural remedies, collectively known as “Ayurveda,” to address various health issues effectively. However, the current generation tends to prioritize chemical-based medicines, commonly referred to as “English Medicine,” due to their rapid recovery rates. Unfortunately, these chemical remedies often come with side effects and steep costs, limiting their long-term viability. To bridge the gap between traditional wisdom and modern healthcare, we propose an automated system for identifying medicinal leaves using computer vision technology. The system requires an extensive dataset comprising diverse images of different medicinal plant species to accurately learn essential features for recognition. By automating this task, we aim to empower individuals to quickly identify medicinal plants and understand their inherent therapeutic values. The proposed work will greatly benefit current and future generation as it will help them to know what kind of a plant it is. In this way it might reduce the gap between the human and the nature.