Objective To construct and validate a nomogram model for predicting the risk of central precocious puberty （CPP） in girls with early breast development， to establish a quantifiable and visual dynamic risk assessment tool and provide evidence-based support for the selecting the timing of individualized intervention. Methods A total of 162 girls with early breast development who visited the Pediatrics Department of Hebei Provincial People's Hospital from September 2023 to December 2024 were retrospectively included. Based on pubertal development status and the results of the gonadotropin-releasing hormone stimulation test， the subjects were divided into an isolated premature thelarche （IPT） group （59 cases） and the CPP group （103 cases）. Clinical data were compared between the two groups. Predictors were screened using binary logistic regression and LASSO regression. A nomogram model was constructed， and its performance was evaluated using the receiver operating characteristic （ROC） curve， calibration curve， and decision curve analysis. Results Statistical analysis revealed significant differences between the two groups in height standard deviation score， weight standard deviation score， bone age， bone age advancement， bone age index， the number of follicles greater than 4 mm， uterine volume， estradiol， insulin-like growth factor 1 （IGF-1）， basal luteinizing hormone （LH） level， basal follicle-stimulating hormone （FSH） level， LH/FSH ratio， LH peak， FSH peak， and LH peak/FSH peak ratio （P < 0.05）. Four independent predictors of basal LH level， height standard deviation score， IGF-1， and the number of follicles greater than 4mm were screened out. The nomogram model showed an AUC of 0.932， at a probability threshold of 0.414，the sensitivity was 95.1%， the specificity was 78.0%， the model demonstrated good calibration and the clinical net benefit rate was 54.6%. Conclusions The nomogram model incorporating basal LH level， height standard deviation score， IGF-1 and the number of follicles greater than 4mm can effectively predict the risk of central precocious puberty in girls with early breast development. It provides a practical tool for non-invasive screening and facilitates early clinical intervention.