Conceptual cost estimates are developed at the early stages of projects. Probabilistic cost estimation is one of the commonly used techniques for quantifying uncertainties included in the early cost estimates. Regression analysis is another modeling technique used for conceptual cost estimating. Neural networks are a form of artificial intelligence which could also be used for conceptual cost estimation. One of the most commonly used conceptual cost estimation technique is the Monte Carlo simulation. Range estimation could be performed easily with the use of a simulation software after the probability distribution functions for the costs are selected. Selection of the proper technique for conceptual cost estimation modeling depends on the availability of the data and also on the purpose of the estimate. Compilation of past project cost data is also very important for early cost estimation, as accuracy of the conceptual estimation models depend on the availability of the historical cost data.