Local forced and mixed heat transfer coefficients were measured by Ghajar and Tam [5] in a horizontal circular straight tube fitted with reentrant, square-edged, and bell-mouth inlets under uniform wall heat flux boundary condition. For the experiments, the Reynolds, Prandtl, and Grashof numbers varied from about 280 to 49000, 4 to 158, and 1000 to 2.5 × 105, respectively. The heat transfer transition regions were established by observing the change in the heat transfer behavior. The data in the transition region were correlated by using the traditional least squares method. The correlation predicted the transitional data with an average absolute deviation of about 8%. However, about 30% of the data in the transition region were predicted with 10–20% deviation, and about 3% with deviations greater than 20%. This is due to the abrupt change in the heat transfer characteristic and its intermittent behavior in this region. Since the value of the heat transfer coefficient has a direct impact on the size of the heat exchanger, a more accurate correlation has been developed using artificial neural networks. A total of 1290 data points (441 for reentrant, 416 for square-edged, and 433 for bell-mouth) were used. The accuracy of the improved heat transfer correlation is excellent, with the majority of the data points predicted with less than 5% deviation.