A method for predicting a price of any subtractively manufactured part utilizing artificial intelligence at a computing device. The method comprises receiving a manufacturing request datum, wherein the manufacturing request datum further comprises at least an element of user mechanical part data, selecting a correlated dataset containing a plurality of data entries. The method further comprises generating, at a clustering unsupervised machine-learning model, at least a first correlated compatible part element, receiving, at a supervised machine-learning model, a first training set, generating, at a supervised machine-learning model as a function of the first training set, an external price output, and determining a price ratio output, wherein determining the price ratio output further comprises generating a loss function of a part specific variable and minimizing the loss function.