Precision medicine represents a transformative paradigm in healthcare, shifting from the traditional "one-size-fits-all" approach toward individualized therapeutic strategies tailored to each patient's unique molecular, genetic, and clinical profile. This special issue brings together cutting-edge research on the computational tools and predictive models that are accelerating this revolution. The integration of multi-omics data has created a wealth of information that demands sophisticated analytical frameworks to extract clinically actionable insights from high-dimensional datasets. Machine learning algorithms, network-based approaches, and systems biology models have emerged as essential instruments for biomarker discovery, patient stratification, and treatment response prediction. Beyond cancer, precision approaches are reshaping the management of rare diseases, pharmacogenomics, and infectious diseases. The microbiome has emerged as a critical modulator of drug response and disease susceptibility, adding another layer of complexity to personalized interventions. This special issue examines innovative methodologies spanning from algorithm development to application development, emphasizing the translational potential of computational approaches. We welcome algorithms, software, R packages, Python libraries, drug repurposing methodologies, and databases that help navigate the labyrinth of personalized medicine. We are focused not only on methodological contribution, but also on its practical application. The contributions herein reflect our collective progress toward a future where every patient receives the right treatment at the right time.