OBJECTIVES To produce a modern, accessible, quick and intuitive growth prediction tool in which growth prediction models (GPMs) were clinically validated. METHODS GPMs support physicians to optimise and monitor GH treatment and response. They are validated, providing accurate predictions of growth response following GH treatment in children with idiopathic growth hormone deficiency (IGHD), Turner syndrome (TS) and short children born small for gestational age (SGA). By using GPMs, realistic expectations of treatment outcomes are conveyed to patients and parents (important as children respond differently to treatment). A modern platform, a website, will host iGRO; the software should ensure web browser compatibility in European endocrine clinics . An internal paediatric endocrinologist robustly tested the GPMs. User acceptance testing (UAT) for acceptability and usability was conducted with external paediatric endocrinologists. These outputs contribute to the Class I medical device Technical File; a requirement for iGRO. RESULTS The clinical validation performed under simulated conditions using the final medical device software passed, consistent with regulatory expectations. GPMs for IGHD, SGA, TS were tested for prediction accuracy. Validation acceptance criteria and test results were included in the test script records. UAT was designed and executed following a rigorous software development lifecycle methodology to ensure completeness of the tool and the specified business and user requirements. UAT was certified through role based testing scenarios (requirements and processes for daily use). The tool, accessed via a secure password protected website, was easily navigated and provided a clear interface requiring little training. Data entry was quick and growth outcomes (i.e. graphical comparisons between patient's actual growth response and one-year predictions) were easily viewed CONCLUSIONS iGRO, an accessible web-based software medical device, provides accurate growth prediction which enable physicians to monitor patients' response to GH treatment. It may potentially be used to detect discrepancies early.