BACKGROUND: Sexual health (SH) services increasingly need to prioritise those at greatest risk of sexually transmitted infections (STIs). We used SH surveillance data to develop algorithms to triage individuals attending SH services within two high-risk populations: men who have sex with men (MSM) and young people (YP). METHODS: Separate multivariable logistic regression models for MSM and YP were developed using surveillance data on demographics, recent sexual history, prior STI diagnoses and drug/alcohol use from five clinics in 2015-2016 to identify factors associated with new STI diagnoses. The models were prospectively applied in one SH clinic in May 2017 as an external validation. FINDINGS: 9530 YP and 1448 MSM SH episodes informed model development. For YP, factors associated with new STI diagnosis (overall prevalence: 10.6%) were being of black or mixed white/black ethnicity; history of chlamydia diagnosis (previous year); and multiple partners/new partner (previous 3-months). The YPs model had reasonable performance (c-statistic: 0.703), but poor discrimination when externally validated (c-statistic: 0.539). For MSM, being of South Asian ethnicity; being born in Europe (excluding the UK); and condomless anal sex or drug use (both in previous 3-months) were associated with STI diagnosis (overall prevalence: 22.0%). The MSM model had a c-statistic of 0.676, reducing to 0.579 on validation. INTERPRETATION: SH surveillance data, including limited behavioural data, enabled triage algorithms to be developed, but its implementation may be problematic due to poor external performance. This approach may be more suitable to self-triage, including online, ensuring patients are directed towards appropriate services. FUNDING: NIHR HTA programme (12/191/05).