Aviation Industry is growing in an unprecedented pace in the twenty first century. Today, over 1000 commercial airlines operate more than 15,000 aircrafts, carrying 3.1billion people and 51.7m tons of freight every year. Therefore air traffic analysis is a critical exercise for both airlines and the concerned civil aviation authority. China, India and Brazil are the three countries closely watched by economists, sociologists and political observers, seen as key indicators of the new world economic order. Air traffic growth and air transportation networks in these three countries is amplifying every day. The fundamental research question being asked in this thesis, is what are the major aviation activity parameters and measures of forecast in these three countries and how can an econometric model be developed to forecast the air traffic demand? In response to the research question, this thesis addresses analyzing and forecasting air travel market in China, India and Brazil using econometric models. Historic air traffic demand data from the year 1970 to 2014 is used to analyze and understand the key demand factors affecting scheduled aviation market in India, China and Brazil. With the decisive factors determined, an attempt is made to develop diverse econometric models for the air travel demand with different combinations of explanatory variables utilizing stepwise regression technique. Multiple regression analysis is performed on the different econometric models developed in order to find the most appropriate model using adjusted R^2 value . A five year forecast (short term) is executed using the most appropriate model econometric model to estimate scheduled air traffic demand in the three countries. The forecasting results can be used by OEM (Original Equipment Manufacturer) like Airbus and Boeing or concerned civil aviation authorities and airlines to perform market study and thereby ensuring the air traffic demand is well matched with the supply.