The heat and mass transfer processes in direct contact membrane distillation (MD) under laminar flow conditions have been analyzed by computational fluid dynamics (CFD). A two-dimensional heat transfer model was developed by coupling the latent heat, which is generated during the MD process, into the energy conservation equation. In combination with the Navies–Stokes equations, the thermal boundary layer build-up, membrane wall temperatures, temperature polarization coefficient (TPC), local heat transfer coefficients, local mass fluxes as well as the thermal efficiency, etc. were predicted under counter-current flow conditions. The overall performance predicted by the model, in terms of fluxes and temperatures, was verified by single hollow fiber experiments with feed in the shell and permeate in the lumen. Simulations using the model provide insights into counter-current direct contact MD. Based on the predicted temperature profiles, the local heat fluxes are found to increase and then decrease along the fiber length. The deviation of the membrane wall temperature from the fluid bulk phase on the feed and the permeate sides predicts the temperature polarization (TP) effect. The TP coefficient decreases initially and then increase along the fiber length. It is also found that the local Nusselt numbers (Nu) present the highest values at the entrances of the feed/permeate sides. Under the assumed operating conditions, the feed side heat transfer coefficients hf are typically half the hp in the permeate side, suggesting that the shell-side hydrodynamics play an important role in improving the heat transfer in this MD configuration. The model also shows how the mass transfer rate and the thermal efficiency are affected by the operating conditions. Operating the module at higher feed/permeate circulation velocities enhances transmembrane flux; however, the thermal efficiency decreases due to the greater heat loss at a higher permeate velocity. The current study suggests that the CFD simulations can provide qualitative predictions on the influences of various factors on MD performance, which can guide future work on the hollow fiber module design, module scale-up and process optimization to facilitate MD commercialization.