Abstract: Order entry apparatus for automatic estimation a transformation model comprising a pattern composed of a plurality of parameters representing custom product specifications, production line conditions and factors for composing the estimates for production cost and completion date. The parameters of this transformation model are specified by learning, leading to estimation for the requested product specifications, in broad consideration of conditions such as those of the production line. The use of a neural network model as this pattern transformation model makes pattern transformation more flexible and pattern learning more efficient. Estimation accuracy is also increased by entering values of predicted charges in production line conditions such as loads or stock obtained from resource requirements planning, process design, capacity requirements planning, etc.