Acute mountain sickness (AMS) is a well‐studied illness defined by clinical features (e.g., headache and nausea), as assessed by the Lake Louise score (LLS). Although obvious in its severe form, early stages of AMS are poorly defined and easily confused with common travel‐related conditions. Measurement of hypoxaemia, the cause of AMS, should be helpful, yet to date its utility for identifying AMS susceptibility remains unclear. This study quantified altitude‐induced hypoxaemia in individuals during an ascent to 4800 m to determine the utility of nocturnal pulse oximetry measurements for prediction of AMS. Eighteen individuals (36 ± 16 years of age) ascended to 4800 m over 12 days. Symptomology of AMS was assessed each morning via LLS criteria, with participants categorized as either AMS‐positive (LLS ≥ 3 with headache) or AMS‐negative. Overnight peripheral oxygen saturations (ov‐ S p O 2 ${{S}_{{\mathrm{p}}{{{\mathrm{O}}}_2}}}$ ) were recorded continuously (1 Hz) using portable oximeters. Derivatives of these recordings were compared between AMS‐positive and ‐negative subjects (Mann–Whitney U‐test). Exploratory analyses (Pearson's) were conducted to investigate relationships between overnight parameters and AMS severity. Overnight derivatives, including ov‐ S p O 2 ${{S}_{{\mathrm{p}}{{{\mathrm{O}}}_2}}}$ , heart rate/ov‐ S p O 2 ${{S}_{{\mathrm{p}}{{{\mathrm{O}}}_2}}}$ , variance, oxygen desaturation index, hypoxic burden and total sleep time at <80% S p O 2 ${{S}_{{\mathrm{p}}{{{\mathrm{O}}}_2}}}$ , all differed significantly between AMS‐positive and ‐negative subjects (all P < 0.01), with cumulative/relative frequency plots highlighting these differences visually. Exploratory analysis revealed that ov‐ S p O 2 ${{S}_{{\mathrm{p}}{{{\mathrm{O}}}_2}}}$ from 3850 m was correlated with peak LLS at 4800 m (r = 0.58–0.61). The findings highlight the potential for overnight oximetry to predict AMS susceptibility during ascent to high altitude. Further investigation is required to develop, evaluate and optimize predictive models to improve AMS management and prevention.