In geotechnical engineering, slope stability back-analysis is widely performed as a type of inverse problem. Three major slope stability parameters are estimated: (i) soil shear strength parameters, (ii) pore water pressure, and (iii) failure model validation. A factor of safety equal to one and the failure surface geometry are the input variables when the Limit Equilibrium Method is employed. However, due to the method constraints, a major drawback of traditional back-analysis has been recognized: deterministic reliable information about shear strength and pore water pressure is required before performing back-analysis. Additionally, slope stability back-analysis has been focused both, on saturated and dry soil conditions. Unsaturated soils have received less attention, perhaps because of its complex behavior. In this study, unsaturated soil shear strength parameters and pore water pressure conditions were estimated from slope stability back-analysis. An infinite slope and steady-state water flow through an unsaturated soil was considered. The inverse problem theory was modelled within a Bayesian framework to perform the slope stability back-analysis. The results show that unsaturated soil shear strength parameters and unsaturated soil conditions at the moment of failure can be estimated via the Bayesian inverse modelling. Unlike traditional slope stability back analysis, Bayesian framework recognizes the uncertainty in the values of the soil properties and ground water conditions before performing the back-analysis.