Waste management has been rapidly increasing worldwide lately due to the skyrocketing waste production and environmental and health-related issues. However, solving this issue using conventional approaches is not feasible. Various efforts are being made to make it more accessible through better technology, including automation. In this research, the Deep Neural Networks (DNN) techniques are utilized to classify waste with the help of image data. The proposed method is tested using multiple experiments for different waste classification tasks, including separating recyclables and organics from the waste. Different models, such as CNN, InceptionV3, ResNet50, and VGG16 are trained for the classification task. The presented work contributes to understanding the advancement of technology use in one of our generation’s most critical challenges – waste management. The obtained findings indicate an effective utilization of DNNs to acquire the necessary knowledge to enhance our future with more sustainable technologies.