Globally, adult mental health problems continue to rise year-on year. The onset of these problems is frequently in the first two decades of life, determined by a complex interplay of nature and nurture. Platforms including linked multi-agency data provide an important opportunity to understand the mechanisms of child mental ill-health and build digital tools to support early identification. However, accessing, linking and analysing such data is beset with significant technological and governance challenges. The public must also be engaged and find solutions acceptable. The FAIR TREATMENT project was designed to tackle these issues by building a demonstrator able to develop prediction models for child mental health using linked multi-agency data across a federated network. This report details the project's findings. This work was funded by UK Research & Innovation [Grant Number MC_PC_21025] as part of Phase 1 of the DARE UK (Data and Analytics Research Environments UK) programme, which is delivered in partnership with Health Data Research UK (HDR UK) and ADR UK (Administrative Data Research UK). In addition, it brings together several other organisations such as the Anna Freud National Centre for Children and Families, Intermine, AIMES, Bitfount, the Universities of Essex and Birmingham and Information Governance Services.