To prepare measures for washing synthetic fibers, which cause proliferation of microplastics in the marine ecosystem, a fundamental analysis is required. Therefore, this study established an efficient method for quantitatively analyzing microfibers using artificial neural networks, comparing the amounts of microfibers generated in the manufacturing, wearing, and washing processes of clothing. The proportion of microfiber emitted during the manufacturing process was the largest (49%), followed by that emitted during the washing (28%) and wearing (23%) processes. This suggests that minimizing the amount of microfiber emitted during the manufacturing process is key to solving microfiber issues in the fashion industry. Additionally, during the wearing process, the amount of waterborne microfiber detected in washing was slightly larger than the amount of airborne microfiber. In the washing process, the washing temperature did not significantly affect microfiber emissions. However, when reducing the amount of water used or increasing the number of washings, microfiber emissions increased noticeably due to the greater friction applied to clothes. A common result of all experiments was that the largest proportion of microfibers was released during the first five washing cycles. Therefore, before wearing new items, consumers can minimize microfiber release by pre-washing using a laundry bag that filters microfibers. Furthermore, the most effective way to minimize microfibers is to eliminate them from the manufacturing process before they are distributed to consumers.