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One-third of infertile couples struggle to conceive despite normal examination and tests. For men, semen analysis is the only widely-adopted diagnostic tool to assess male infertility. However, it is unable to detect abnormal sperm function or accurately predict pregnancy except in cases of complete absence of sperm. Sperm function tests (SFT) could help by directing treatment to intracytoplasmic sperm injection where indicated, improving treatment efficiency and reducing overall cost. However, SFT are not currently routinely used in clinical practice. We developed a classification and regression tree model to compare current and alternative fertility treatment pathways from the UK NHS payer perspective over a short-term time horizon covering up to three funded IVF or ICSI cycles. A one-way sensitivity analysis was then performed to evaluate the model’s robustness. Our model shows that SFT could reduce unnecessary treatment cycles and lower average treatment costs. The base-case model using CatFlux test was associated with a small cost increase at a lower assumed prevalence rate (£9.31 per couple) and cost savings at a higher prevalence rate (£26.65 per couple). One-way sensitivity analysis showed that results were robust to plausible variation in most parameters, with incremental costs remaining close to cost neutrality across scenarios. The model was most sensitive to the probability of pregnancy following ICSI while variation in IVF and ICSI costs and fertilisation failure probabilities had limited impact on results. Based on 18,000 fresh IVF cycles in 2023 alone, this corresponds to a financial impact for the UK NHS ranging from an additional cost of £167,500 to a cost saving of £479,700. Beyond economic benefits, reliable SFT would improve overall treatment success by reducing IVF affected by fertilisation failure, enabling targeted selection of medically assisted reproduction (MAR) and faster time to pregnancy. It spares countless couples the emotional distress, financial burden, and health risks associated with repeated fertility treatments. Based on a clinical pathway model, integrating SFT into fertility treatment pathways has the potential to generate savings for healthcare systems. More importantly, it enables personalised and precise MAR, reducing the risks and inefficiencies of trial-and-error treatment cycles as well as improving patient outcomes.