The Harmful Airborne Fungal Spores (HAFS) can cause a condition in which an immune reaction is triggered due to foreign substance encounter, known as immunoglobulin E (IgE) sensitization. However, the severity depends on the spore type and amount in the air. Information on the abundance of spores is not available at local scale due to a scarcity of costly in-situ monitoring facilities. UMMC, along with its partners, is engaged in developing a HAFS estimation method that can be used to learn about the abundance of HAFS at local scale.Recently, UMMC has employed a Machine Learning method, in collaboration with UTD, utilizing more than eighty environmental variables that are associated with the growth and dispersion of mold spores in outdoor environments. With about 300 training data, collected from UMMC's six spore collection sites using Burkard spore traps, a very promising result has been achieved with correlation coefficient of 0.8 and higher for different genus of HAFS. UMMC is now seeking funding support to collect more training data in order to develop an operational model to estimate HAFS for public health applications.