The engineering economics procedures for evaluation of processes and systems that are characterized by distributed variables are considered. The economic moment of a distributed process variable is defined and its normalized function is shown to be part of the family of Moment Distribution Functions (MDF). The MDF provides data concerning the distribution of the economic value which is assigned to the random process variable. This data is necessary to specify which part of the distribution carries a higher proportion of this economic value, and hence should have a higher impact on the process design and evaluation procedures. Engineering economics criteria which involve the optimization of the expectation of cost and profit and on the application of the MDF are formulated and compared. The criteria which involve the MDF provide acceptance domains as well as the probability that this domain will be materialized. The acceptance domain, which satisfies the condition that the MDF exceeds a prescribed level, reflects an economic potential of the random variable, whereas the probability of its realization is related to the risk involved in setting this prescribed level for the potential. As the economic potential is ordinarily a descending function of the probability of its materialization and vice versa, the trade off between them is a matter of policy. Examples of the application of the different engineering economics criteria in conjunction with known probability density functions are provided. Distributed flows in a pipe are analyzed and the optimum pipe diameter is shown to depend on the parameters characterizing the random flow. Financial and growth compounding factors that depend on distributed interest and growth rate per unit time are considered. It is shown that application of MDF of the compounding factors for evaluation of the expected growth rate is superior to the use of the original distribution to this end.