The real-time identification of medicinal plants holds substantial significance in various domains such as ethno botany, pharmaceuticals, and traditional medicine. This paper proposes an innovative approach that leverages deep learning techniques to achieve swift and accurate identification of medicinal plant species. Traditional methods of plant identification are often time-consuming and require specialized botanical expertise. In contrast, our proposed DL-based system harnesses the power of computer vision and pattern recognition to instantly recognize medicinal plants directly from visual input, such as images of leaves, flowers, or whole plants. It employs deep learning architectures that enable the model to automatically learn distinctive features and patterns unique to each plant species. This research introduces an intelligent vision-based system designed to recognize herb plants through the creation of an automated Convolutional Neural Network (CNN). The articulated deep learning model incorporates a CNN block dedicated to the extraction of relevant features.