A steel pipe manufacturing method comprising: determining a coated steel pipe manufacturing condition in accordance with a steel pipe manufacturing characteristic determined by a steel pipe manufacturing characteristics determination; and manufacturing an anticorrosion-coated steel pipe for use in constructing a submarine pipeline under the determined coated steel pipe manufacturing condition, wherein said steel pipe manufacturing characteristics determination comprises: sequentially changing at least one of a steel pipe shape after steel pipe forming, a steel pipe strength characteristic after steel pipe forming, a pipe-making strain during steel pipe forming, a coating condition, and a bending strain during construction included in a steel pipe manufacturing characteristic such that a predicted coated steel pipe collapse strength under external pressure bending by a steel pipe collapse strength prediction asymptotically approaches a requested collapse strength under external pressure bending of an intended coated steel pipe, to determine a steel pipe manufacturing characteristic, wherein said steel pipe collapse strength prediction comprises: inputting, into a generated steel pipe collapse strength prediction model a steel pipe manufacturing characteristic including a steel pipe shape of a coated steel pipe to be predicted after steel pipe forming, a steel pipe strength characteristic after steel pipe forming, a pipe-making strain during steel pipe forming, a coating condition, and a bending strain during construction, to predict a collapse strength under external pressure bending of a coated steel pipe coated after steel pipe forming, and wherein generating said steel pipe collapse strength prediction model comprises: performing machine learning of a plurality of learning data that include, as an input datum, a previous steel pipe manufacturing characteristic including a steel pipe shape after steel pipe forming, a steel pipe strength characteristic after steel pipe forming, a pipe-making strain during steel pipe forming, a coating condition, and a bending strain during construction and, as an output datum, a previous collapse strength under external pressure bending of a coated steel pipe coated after steel pipe forming, to generate a steel pipe collapse strength prediction model that predicts a collapse strength under external pressure bending of a coated steel pipe coated after steel pipe forming. determining a coated steel pipe manufacturing condition in accordance with a steel pipe manufacturing characteristic determined by a steel pipe manufacturing characteristics determination; and manufacturing an anticorrosion-coated steel pipe for use in constructing a submarine pipeline under the determined coated steel pipe manufacturing condition, wherein said steel pipe manufacturing characteristics determination comprises: sequentially changing at least one of a steel pipe shape after steel pipe forming, a steel pipe strength characteristic after steel pipe forming, a pipe-making strain during steel pipe forming, a coating condition, and a bending strain during construction included in a steel pipe manufacturing characteristic such that a predicted coated steel pipe collapse strength under external pressure bending by a steel pipe collapse strength prediction asymptotically approaches a requested collapse strength under external pressure bending of an intended coated steel pipe, to determine a steel pipe manufacturing characteristic, wherein said steel pipe collapse strength prediction comprises: inputting, into a generated steel pipe collapse strength prediction model a steel pipe manufacturing characteristic including a steel pipe shape of a coated steel pipe to be predicted after steel pipe forming, a steel pipe strength characteristic after steel pipe forming, a pipe-making strain during steel pipe forming, a coating condition, and a bending strain during construction, to predict a collapse strength under external pressure bending of a coated steel pipe coated after steel pipe forming, and wherein generating said steel pipe collapse strength prediction model comprises: performing machine learning of a plurality of learning data that include, as an input datum, a previous steel pipe manufacturing characteristic including a steel pipe shape after steel pipe forming, a steel pipe strength characteristic after steel pipe forming, a pipe-making strain during steel pipe forming, a coating condition, and a bending strain during construction and, as an output datum, a previous collapse strength under external pressure bending of a coated steel pipe coated after steel pipe forming, to generate a steel pipe collapse strength prediction model that predicts a collapse strength under external pressure bending of a coated steel pipe coated after steel pipe forming.