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In July 2020, NASA’s Perseverance (Mars 2020) mission was launched. The rover sent to the surface of Mars will not only perform in situ analyses, but will also collect rock and regolith samples that will be returned to Earth by future missions for further investigations. Therefore, the amount and quality of astrobiological data retrieved from these missions is expected to be unprecedented. The challenge faced by the astrobiology community will be to use these data in the most efficient way to assess whether any of the analysed samples are of biogenic origin. However, in situ biogenic assessments often lack quantitative support. Particularly, their statistical uncertainty is not systematically evaluated. This study aims to provide the first quantitative framework that evaluates the uncertainty of in situ biogenic assessments using recursive Bayesian statistics. Our results show that detecting more than seven potential biosignatures does not increase the reliability of biogenic assessments, unless the probability of detection of biosignatures in the sample and the probability of the biosignatures being false positives are well constrained. This study emphasizes the need for quantitative support of biogenic assessments and astrobiology strategies in general.