Abstract: The invention discloses a model based on machine learning-radiomics which is a Nomogram model; the establishment of said Nomogram model comprising following steps: S1. collecting data and predicting factor selection; S2. combining selected 6 radiomics characteristics according to contribution weighting, developing a rad-score model; S3. establishing different diagnosis models, comparing performances of the diagnosis models in the diagnosis of osteoporosis and osteopenia, wherein said diagnosis models comprise: Clinics model, Radiomics model, and Combined model; S4. performing visualization processing on combined model by using the “rms” packet in R software to obtain Nomogram model; S5. validation of the Nomogram model. The invention combines characteristics of the radiomics and clinical risk factors to establish a combined Nomogram model to diagnose conditions of osteoporosis and osteopenia of patients.