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In the current situation, the timely diagnosis of cancer helps to increase the survival rate of the patients. The most common cancer in women is breast cancer. The histopathological images of the breast help in the diagnosis of breast cancer. In this work, the histopathological stained images are used to build a pretrained deep learning model for the prediction of breast cancer. The major pretrained models like Inception V3, AlexNet, MobileNetV2, VGG16, and ResNet are used for model building. For breast cancer segmentation of histopathological images, segmented regions are obtained using both U-Net and R2U-Net models. For classification, pretrained models like Inception V3, MobileNet, AlexNet, VGG net, and ResNet were used. The highest accuracy was for ResNet of 89% and the least accuracy for MobileNet of 78% for breast cancer classification using histopathological images.