BlebNet is an open-source software tool designed for the automated identification and quantification of axonal swellings, also known as ovoids or blebs, in axons from fluorescent microscope images. Developed as a convolutional neural network (CNN) with a UNet architecture, it is particularly effective for analyzing whole mount optic nerves. This tool is part of a comprehensive toolkit for 3-dimensional immunostaining, enabling rapid and automated quantification of axonal defects. It can be adapted for monitoring axonal degeneration and inflammation across various neurodegenerative disease models, offering higher sensitivity for feature detection compared to traditional manual quantification methods. BlebNet addresses the challenges of time-consuming and potentially biased manual analysis of tissue sections, providing a robust solution for researchers studying neurofilament-labeled optic nerves and similar structures.