Crude oil viscosity is an important physical property that controls and influences the flow of oil through porous media and pipelines. Hence, it is the basis of many reservoir engineering and production system calculations. In the crude oil recovery and processing, viscosity is a significant parameter because a large amount of time and money are spent in experimental measurements of viscosity. This necessitates the development of reliable viscosity models capable of predicting crude oil viscosity and reduces the expensive and cumbersome experimental measurements. Because of the complexities and varied composition of crude oils, empirical models and other predictive tools cannot replace the laboratory measurements, even if the latter is costly. This paper presents new compositional models for estimating crude oil viscosity. The new models use fluid composition, temperature, and pressure to predict the oil viscosity. The models were derived from viscosity measurements of several crudes from the Middle East, the North Sea, and others. The accuracy of the proposed models has been compared to that for several empirical correlations, corresponding state models, and equation of state based viscosity models. The comparison shows the superiority of the new models over the other methods.