SonoPhenoScan is a dedicated ultrasonic vocalization detection and analysis module, purpose-built for preclinical and translational research where subtle changes in communication matter. Using high-sensitivity ultrasonic microphones and AI-driven signal processing, the system automatically detects, classifies, and quantifies high-frequency calls across a wide range of paradigms, including social interaction, anxiety, pain, neurodevelopmental, and neurodegenerative models. Researchers can reliably separate call types, extract detailed temporal and spectral features, and correlate vocalization patterns with behavioral events or pharmacological interventions, all without manual scoring. Flexible configuration options support mice, rats, and other small animals in both standard and custom arenas, from home cages to specialized test chambers. Intuitive visualization tools, synchronized audio–video review, and exportable data formats make it easy to integrate SonoPhenoScan output into existing analysis pipelines, LIMS, and statistical workflows. By combining precise hardware, robust algorithms, and streamlined reporting, SonoPhenoScan delivers research-grade accuracy, improves reproducibility, and significantly reduces analysis time, enabling laboratories to scale up studies, standardize protocols across sites, and uncover subtle phenotypes that might otherwise be missed.