Urinary tract infection (UTI) is among the commonest causes of febrile illness in children of less than five years of age and the most common bacterial infections during pregnancy accounting for approximately 10% of hospital visits by women in Sub-Saharan Countries. Thus early-diagnosis and appropriate treatment of UTI is essential in order to avoid long term complications. However, most rural areas in Sub-Saharan Countries. lack medical professionals and laboratory facilities to enable timely UTI diagnosis. The research projects aim to leverage the well-established machine learning algorithms for the timely diagnosis of UTI. Machine learning (ML) has been applied successfully to solve complex problem ranging from speech processing, image recognition and in drug discovery just to mention few. Motivated by these AI/ML achievements, we aim to build machine intelligence and mobile based system to improve and facilitate timely UTI diagnosis especially in rural areas.