Objective Minimal change disease (MCD) is one of the main causes of idiopathic nephrotic syndrome (NS). Renal biopsy has been the gold standard for clinical diagnosis of MCD. Because renal biopsy causes substantial harm to patients, this study aims to establish a mathematical diagnostic model based on biological parameters to achieve noninvasive diagnosis of MCD. Methods The AUC was used to evaluate the biological parameters for the differentiation between the MCD group and the control group in 798 patients with idiopathic nephrotic syndrome. Logistic regression methods were used to establish diagnostic models and calculate the Youden index, sensitivity, specificity, and accuracy to assess the clinical diagnostic value of the model. Results The AUC of seven biological parameters was greater than 0.70, including albumin (AUC=0.821), total cholesterol (AUC=0.800), plasma fibrinogen (AUC=0.706), high density lipoprotein cholesterol (AUC=0.747), low density lipoprotein cholesterol (AUC=0.777), total protein (AUC=0.824), and thrombin time (AUC=0.804). Further analysis showed that total cholesterol, high density lipoprotein cholesterol and thrombin time were risk factors for MCD, and total protein was a protective factor for MCD. The optimized logistic regression model includes four biological parameters (total cholesterol, high density lipoprotein cholesterol, total protein, and thrombin time). The model has an AUC of 0.870, an Youden index at the optimal cutoff point of 0.617, a sensitivity of 80.43%, a specificity of 81.31%, an accuracy of 81.26%, and an associated criterion of 0.073 5, which means that if PRE2>0.073 5, MCD patients will be determined, otherwise they will be other kidney disease patients. Conclusion The 4-parameter logistic regression model established in this study has high accuracy and can be used for clinical diagnosis of MCD.