Abstract: Objective To construct a nomogram model for predicting occupational exposure among public health workers and to provide scientific evidence for exposure risk prediction and prevention. Methods A convenience sampling method was used to survey 640 public health workers in Shijingshan District, Beijing, from July 2023 to June 2024. Data were collected using a general information questionnaire and the Occupational Exposure Survey for Healthcare Workers (OESHW) to assess occupational exposure. Univariate analysis and multivariate logistic regression were performed to identify influencing factors, which were then used to construct a nomogram model, and its performance was evaluated. Results A total of 631 valid questionnaires were collected, with a valid response rate of 98.6%. In the past year, 186 respondents (29.5%) reported experiencing occupational exposure, including mucosal exposure (64 cases, 34.4%), exposure via damaged skin (43 cases, 23.1%), sharps injuries (40 cases, 21.5%), and other exposures (39 cases, 21.0%). Among these, 86 individuals (46.2%) did not report or address the exposure in a timely manner. Logistic regression analysis showed that for each additional year of work experience, the risk of occupational exposure decreased (OR = 0.728). Compared with workers holding an associate degree or below, those with a bachelor’s degree and those with a master’s degree or above had reduced risks to 0.910 and 0.904 times, respectively. Compared to those with junior professional titles or below, those with intermediate and senior titles had lower risks of 0.924 and 0.890 times, respectively. However, each one-point increase in the OESHW total score was associated with a 2.751-fold increase in the risk of occupational exposure (all P < 0.05). A nomogram model incorporating these predictors achieved a concordance index (C-index) of 0.89, with a sensitivity of 84.9% and specificity of 86.7%. Conclusions The incidence of occupational exposure among public health workers in Shijingshan District, Beijing, was relatively high. Longer work experience, higher education levels, and advanced professional titles were protective factors, while higher OESHW scores were risk factors. The developed nomogram demonstrated good discrimination and calibration, indicating strong predictive ability. Public health institutions should enhance occupational risk management, increase training on prevention of occupational exposure, and conduct regular risk assessments to reduce exposure incidence.