Autism spectrum disorder (ASD) is a psychiatric disorder which leads to neurological anddevelopmental growth of a person which starts in early age and gets carried throughout their life.It is a condition associated with significant healthcare costs and early diagnosis can reduce these.Unfortunately, waiting time is lengthy for an ASD diagnosis and it is cost effective. Due to theincrease in economy for autism prediction and the increase in the number of ASD cases across theworld is in need of easily implemented and effective screening methods by GUI results. Toovercome the time complexity for identifying the disorder advanced technologies can be used suchas machine learning algorithms to improve precision, accuracy and quality of the diagnosisprocess. Machine learning helps us by providing intelligent techniques to discover the affectedpatient, which can be utilized in prediction and to improve decision making. And hence, wepropose the data set features related to autism screening of adult and child to be used for furtheranalysis and to improve the classification of ASD cases.