Parkinson's disease is one of the most common neurological disease is considered malicious. Parkinson's disease is a chronic condition and always in progress. The goal of treatment for patients with symptoms but not eliminate the symptoms under control . On the pattern, quantitative structure–activity relationship (QSAR) study has been done on a series of Amid derivatives for the treatment of Parkinson’s disease. The purpose of QSAR study is to find a relation between the composition or structure of a compound with its bio or chemical activity, in order to design a new compound with expected properties or predict the properties of an unknown compound. Up to now, a lot of successful applications have been reported in many different types of cases, e.g., medicine design, environmental chemistry exploration, pesticide searching, etc .The artificial neural networks (ANNs) are known as a good method in expressing highly non-linear relationship between the input and output variables, hence, greater interests were attracted in applying them to the pattern classification of complex compounds Genetic algorithms (GAs) were introduced by Holland. They mimic nature’s evolutionary method of adaptation to a changing environment. GAs are stochastic optimization methods hat provide powerful means to perform directed random searches in a large problem space as encountered in chemometrics and drug design . In multiple linear regression (MLR), for a given data set consisting of a target variable and M descriptors for n compounds, a model is made with good fitting to define the combination of m descriptors (m< M) on target variable. Running through all combinations usually is too time-consuming. Therefore, several approximate methods have been proposed for this reason, but none of them guarantied to find very best combination in all cases.