Background: Li-Fraumeni Syndrome (LFS) is a hereditary cancer syndrome associated with a germline mutation in the TP53 tumor suppressor gene and an increased risk of developing a spectrum of cancers throughout a carrier’s lifetime. Early cancer detection in patients with TP53 mutations can dramatically improve cancer survival rates. However, it can be difficult to identify patients at risk of LFS due to the overlap of the multiple cancer types with other inherited cancer syndromes. Risk prediction modeling has been widely accepted by the clinical community, however, currently there is not an available tool to assist in risk prediction of LFS during genetic counseling sessions. LFSPRO is a statistical model that has previously been validated on large research cohorts in predicting the likelihood of a proband having LFS based off detailed patient and family history information. To improve the clinical utility of LFSPRO, a user-friendly interface is still needed. Additionally, we aim to evaluate concordance between LFSPRO’s abilities in predicting the likelihood of a proband having LFS and currently established clinical testing criteria. Methods: We developed a Shiny App to create a user-friendly interface for genetic counselors (GCs) to run LFSPRO. Determining concordance of LFSPRO to standard germline testing criteria and the clinical utility of the LFSPRO Shiny App is underway by GCs within the Department of Clinical Cancer Genetics at MD Anderson Cancer Center through prospective data collection and completion of user surveys. Following a standard genetic counseling session, individuals identified as concerning for a potential germline TP53 mutation are evaluated with LFSPRO to compare performance of the model to established TP53 testing guidelines. Concordance is then evaluated in prediction of TP53 mutation carrier status from LFSPRO, current clinical criteria and clinical judgment. Data collection began 12/21/2021 and is currently ongoing. Results: Close collaboration with GCs and clinicians on the development of the LFSPRO Shiny App has achieved automated de-identified input data, clear pedigree drawing, important demographic data, interpretable risk results and risk visualizations to be used at the GC's discretion. To date, 29 individual’s family data have been run through LFSPRO. Of these, 11 have not currently completed TP53 testing and concordance cannot be determined. Of the 18 remaining, 14 individuals’ LFSPRO results were concordant with current clinical criteria. Further data collection is needed to appropriately analyze concordance. Conclusions: The LFSPRO Shiny App aims to provide an additional tool for GCs and clinical providers to assess patient risk for LFS. This ongoing study will help establish the clinical utility of LFSPRO in a single institution’s genetic counseling practice with the potential to be applied to other patient care settings in the future.