First flush analysis entails the comparison of pollutographs and hydrographs. The difficulty of this type of analysis also lies in the fact that it runs up against a wide array of experimental uncertainties associated with the collection of temporal data. The present paper proposes a methodology that accounts for the aforementioned factors in the calculation of occurrence probability for first flush as measured at a storm drain inlet. Considering concepts such as standard uncertainty (for first flush uncertainties), the Monte Carlo method, the Spearman correlation rank test and Partial Least Squares Regressions (for analysis of the relationship between precipitation characteristics and first flush). This methodology has been coined "Occurrence probability of First Flush In Storm drain inlets" (OFFIS). Developed in R, OFFIS detected first flush in a specific case study.