Summary A range of mathematical models has been developed to infer whether a species is extinct based on a sighting record. Although observations have variable reliability, current methods for detecting extinction do not differentiate observation qualities. A more suitable approach would consider certain and uncertain sightings throughout the sighting period. We consider a small population system, meaning we assume sighting rates are constant and the population is not declining. Based on such an assumption, we develop a Bayesian method that assumes that certain and uncertain sightings occur independently and at uniform rates. These two types of sightings are connected by a common extinction date. Several rates of false sightings can be calculated to differentiate between observation types. Prior rates of false and true sightings, as well as a prior probability that the species is extant, are included. The model is implemented in OpenBugs, which uses Markov chain Monte Carlo (MCMC). Based on records of variable reliability, we estimate the probability that the following species are extinct: Caribbean seal Monachus tropicalis, grey, black‐footed ferret Mustela nigripes, Audubon & Bachman, greater stick‐nest rat Leporillus conditor, Sturt, and lesser stick‐nest rat Leporillus apicalis, Gould. As further examples, Birdlife International provided the sighting records for the Alaotra grebe Tachybaptus rufolavatus, Delacour, Jamaica petrel Pterodroma caribbaea, Carte, and Pohnpei mountain starling Aplonis pelzelni, Finsch, with prior probabilities for extinction. The results are compared with existing methods, which ignore uncertain sightings. We find that including uncertain sightings can considerably change the probability that the species is extant, in either direction. However, in our examples, including the quality of the uncertain sighting made little difference. When we ignore uncertain sightings, our results agree with existing methods, especially when the last sighting was near the end of the sighting period. Synthesis and applications. Estimating the probability that a species is extinct based on sighting records is important when determining conservation priorities and allocating available resources into management activities. Having a model that allows for certain and uncertain observations throughout the sighting period better accommodates the realities of sighting quality, providing a more reliable basis for decision‐making.