Thermal perception is determined not only by sensitivity but also by precision, yet the latter is often overlooked in thermosensation and pain research. This study examined how ageing and diabetic polyneuropathy (DPN) affect the sensitivity and precision of thermal perception at the volar forearm and whether combining these parameters can aid in distinguishing patients from healthy controls. Using a Bayesian hierarchical modelling approach, we estimated psychometric function thresholds (sensitivity) and slopes (precision) for cold detection, warm detection, cold pain, and heat pain in 86 healthy adults (aged 21–80) and 34 patients with DPN. We assessed age- and neuropathy-related effects on these parameters. We also estimated these parameters separately for each participant and used the resulting estimates in classification analyses, to determine their utility in discriminating patients from controls. Ageing was associated with elevated detection and cold pain thresholds and reduced precision of cold detection. Patients with DPN showed similar patterns: higher detection thresholds and lower cold detection slopes while pain-related parameters were largely unaffected. These findings indicate that ageing and neuropathy produce qualitatively similar changes in thermosensory function, particularly affecting cold detection sensitivity and precision. Classification based on various combinations of thresholds and slopes successfully discriminated patients from controls, with cold detection slopes offering the best performance amongst classification analysis focusing on a single parameter. Combining threshold and slope parameters for a given modality did not significantly improve classification accuracy but combining thresholds and slopes of all modalities led to the best performance, with near perfect classification accuracy (AUROCC: .92, 95% CI [.86,.97]). Modelling both thresholds and slopes provides a more comprehensive view of sensory decline and may enhance the detection of early or subtle sensory dysfunction.