Lower Respiratory System Diseases (LRSD) are one of the most deathcausing diseases in the world. In a large number of cases, people stay unaware of their body reactions and symptoms as they begin with a cold, cough, and fever. These symptoms on later stages lead to cause Chronic Obstructive Pulmonary Diseases (COPD), Influenza, Pneumonia, Asthma, Lung Cancer, and other threatening respiratory tract diseases. Past researches and studies related to Common cold and Influenza show that they have several similarities and can also develop into acute Bronchitis and Pneumonia. There are over 8 million deaths in the year 2016 related to LRS diseases, and these numbers are increasing continuously. The majority of people in the world can not access proper health because it is either expensive, inefficient, or beyond reach. It is essential to take reasonable and modern health care facilities into account when people promote about better future and a healthy lifestyle. In the present-day with technological advancement, the gaps between advanced healthcare and error-free disease diagnosis are closing. However, it is still very challenging to find nearby healthcare to every individual for the survival of their life. Accordingly, many researchers have revealed the importance and effectiveness of an Intelligent System that can assist with the diagnosis of heart diseases, diabetes, and various cancer diseases. The proposed LRSD diagnosis Intelligent System aims to help an ordinary human being to perform diagnosis by herself/himself, and the system can predict the possible outcome of the LRS disease. The proposed Intelligent System consists of 3 three properly connected Fuzzy Inference Systems (FISs) based on the supplied information and parameters using a user-friendly interface. A list of common symptoms has been drawn precisely from expert’s advice and information posted on medical websites for more simplicity and reliable results for this model. A Mamdani FIS provides better fuzzification results with system multiple inputs. To simplify the diagnosis process and to reduce the uncertainty, three Mamdani Fuzzy Inference Systems are proposed in the Thesis to measure the tendency of getting the LRS diseases, the possible risk of getting the Common Cold or Influenza, and the potential risk of getting three types of major respiratory diseases. Additionally, a user-friendly interface is being created for smooth human interaction with the developed system by using the MATLAB software. The designed system determines the possible risk of getting the disease such as Influenza, Acute Bronchitis, and Pneumonia with the help of fuzzification rules and the database created with the field experts’ advice. Results of the diagnosis can help identify the possibility of getting these fatal diseases in earlier stages. Moreover, the developed system is beneficial in such places and societies where it is almost impossible to find the supply of physicians for the timely treatment of any medical disease. Keywords: Fuzzy Logic, Fuzzy Inference System, Lower Respiratory System Disease, Pneumonia, Influenza, MATLAB App Designer