Invasive fungal diseases (IFDs) are opportunistic infections that result in significant morbidity and mortality in pediatric oncology patients. Predictive risk tools for IFD in pediatric cancer are not available. We conducted a 7-year retrospective study of pediatric oncology patients with a diagnosis of febrile neutropenia at UCM Comer Children's Hospitals. Fourteen clinical, laboratory, and treatment-related risk factors for IFD were analyzed. Stepwise variable selection for multiple logistic regression was used to develop a risk prediction model for IFD. Two comparative analyses have been conducted: (i) all suspected IFD cases and (ii) all proven and probable IFD cases. A total of 667 febrile neutropenia episodes were identified in 265 patients. IFD was diagnosed in 62 episodes: 13 proven, 27 probable, and 22 possible. In the final multiple logistic regression models, 5 variables were independently significant for both analyses: fever days, neutropenia days, hypotension, and absolute lymphocyte count <250 at the time of diagnosis. The odds ratio and a relative weight for each factor were then calculated and summed to calculate a predictive score. A risk score of ≤4 and ≤5 (10/11 maximum) for each model signifies low risk, respectively (<1.2% incidence). Model discrimination was evaluated by the area under the receiver operator characteristics curve with an area under the curve of 0.95/0.94 for each model. Our prediction IFD risk models perform well, are easy-to-use, and are based on readily available clinical data. Profound lymphopenia absolute lymphocyte count <250 mm3 could serve as a new important prognostic marker for the development of IFD in pediatric cancer and hematopoietic stem cell transplant patients.