There is a huge demand for the use of spices in South Asian countries. Each spice has a different taste, smell, and quality. People don't recognize spices and don't use them properly which results in not getting their actual qualities and wasting our time. Proper identification of spices is therefore required for use of proper spices. In this research, our proposed model can correctly recognize spices using computer vision and Convolutional Neural Networks (CNNs) with the help of images. there are 8377 images is used for training our custom build CNN architecture. For the best outcome, we have made three different models. And we choose the best model by applying different experimental theories. We obtained some remarkable outcomes from model 3 and, based on a test that which is never been seen before by our model and evaluation results selected the model that best performed. The highest accuracy reached 99.41% by model 3.