Background: Network analysis provides a new viewpoint that explicates intertwined and interrelated symptoms into dynamic causal architectures of symptom clusters. This is a process called ‘symptomics’ and is concurrently applied to various areas of symptomatology. Aims: Using the data from Research on Asian Psychotropic Prescription Patterns for Antipsychotics (REAP-AP), we aimed to estimate a network model of extrapyramidal syndrome in patients with schizophrenia. Methods: Using data from REAP-AP, extrapyramidal symptoms of 1046 Asian patients with schizophrenia were evaluated using the nine items of the Drug-Induced Extrapyramidal Symptoms Scale (DIEPSS). The estimated network of the ordered-categorical DIEPSS items consisted of nodes (symptoms) and edges (interconnections). A community detection algorithm was also used to identify distinctive symptom clusters, and correlation stability coefficients were used to evaluate the centrality stability. Results: An interpretable level of node strength centrality was ensured with a correlation coefficient. An estimated network of extrapyramidal syndrome showed that 26 (72.2%) of all possible 35 edges were estimated to be greater than zero. Dyskinesia was most centrally situated within the estimated network. In addition, earlier antipsychotic-induced extrapyramidal symptoms were divided into three distinctive clusters–extrapyramidal syndrome without parkinsonism, postural instability and gait difficulty-dominant parkinsonism, and tremor-dominant parkinsonism. Conclusions: Our findings showed that dyskinesia is the most central domain in an estimated network structure of extrapyramidal syndrome in Asian patients with schizophrenia. These findings are consistent with the speculation that acute dystonia, akathisia, and parkinsonism could be the risk factors of tardive dyskinesia.