The interpretation of depositional environments provides important information to understand facies distribution and geometry. The classical approach to interpret depositional environments principally relies on the analysis of lithofacies, biofacies and stratigraphic data, among others. An alternative method, based on geochemical data (chemical element data), is advantageous because it can simply, reproducibly and efficiently interpret and refine the interpretation of the depositional environment of carbonate strata. Here we geochemically analyze and statistically model carbonate samples (n = 156) from seven sections of the Arab-D reservoir outcrop analog of central Saudi Arabia, to determine whether the elemental signatures (major, trace and rare earth elements [REEs]) can be effectively used to predict depositional environments. We find that lithofacies associations of the studied outcrop (peritidal to open marine depositional environments) possess altered REE signatures, and that this trend increases stratigraphically from bottom-to-top, which corresponds to an upward shallowing of depositional environments. The relationship between REEs and major, minor and trace elements indicates that contamination by detrital materials is the principal source of REEs, whereas redox condition, marine and diagenetic processes have minimal impact on the relative distribution of REEs in the lithofacies. In a statistical model (factor analysis and logistic regression), REEs, major and trace elements cluster together and serve as markers to differentiate between peritidal and open marine facies and to differentiate between intertidal and subtidal lithofacies within the peritidal facies. The results indicate that statistical modelling of the elemental composition of carbonate strata can be used as a quantitative method to predict depositional environments and regional paleogeography. The significance of this study lies in offering new assessments of the relationships between lithofacies and geochemical elements by using advanced statistical analysis, a method that could be used elsewhere to interpret depositional environment and refine facies models.