International Journal of Machine Learning (IJML) is a peer-reviewed international journal dedicated to advancing theory, methods, and applications in machine learning and artificial intelligence. The journal publishes high-quality original research articles, systematic reviews, and methodological papers in areas including supervised and unsupervised learning, deep learning, reinforcement learning, natural language processing, computer vision, explainable AI, trustworthy AI, and real-world industrial applications. IJML welcomes interdisciplinary contributions that demonstrate scientific rigor, novelty, and practical impact. The journal aims to become a reputable global platform for researchers, academics, and practitioners by upholding strong editorial standards, transparent peer-review processes, research ethics, and international publication best practices.