Determination of the sex of human bone remains represents a crucial stage in any palaeoanthropological study. The palaeobiological or palaeoethnological interpretations depend on its reliability. It is acknowledged that the adult hip-bone (os coxae) is by far the best non-population-specific indicator for reliable sex determination of adults. However, we clarify here a certain number of limitations which lower the reliability and ease of application of the usual methods. We propose a new tool—Probabilistic Sex Diagnosis (DSP: Diagnose Sexuelle Probabiliste)—based on a worldwide hip-bone metrical database (2040 adult specimens of known sex from 12 different reference populations). Sex is determined by comparing the specimen’s measurements to those from the database and by computing the individual probability of being female or male, from any combination of at least four variables among ten. This method is very easy to learn and apply; it provides sex diagnosis for any anatomically modern human, whatever population the specimen belongs to. Numerous combinations allow sex diagnosis of either well—preserved hip-bones or damaged ones. DSP is thus useful for both archaeological and forensic purposes. Its accuracy is close to 100%. The DSP computing program is available at the following web link: http://www.pacea.u-bordeaux1.fr/publication/dspv1.html

Age at death assessment of adult skeletons is one of the most difficult problems in forensic and physical anthropology. Two fundamental sources of error are described: the complex variability in the process of skeletal aging and methodological bias. Taking into account these limits, we developed a new scoring system for the auricular surface of the ilium and the pubic symphysis. In order to address a large variability, we examine reference samples from Europe, North America, Africa, and Asia. Data were processed using Bayesian prediction in order to classify specimens in age range categories. Results show that combining indicators do not perform better than the auricular surface used as a single indicator. Morphological changes with aging are variable between Asian, African, and European populations, confirming the necessity to use population-specific standards. Bayesian prediction produces reliable classification and is applicable for subjects over 50 years old, a real methodological improvement.