Non-communicable diseases can affect a considerable amount of the global population. Chronic kidney disease is one of such significant contributors to morbidity and mortality. A delay in diagnosing the disease can lead to human loss as well. Machine Learning algorithms are exhibiting remarkable interventions in the field of medicine by detecting abnormalities and performing classification tasks with proper accuracy. Employing a diverse dataset which has all the necessary features that are obtained from demographic, clinical, and laboratory data. The objective is to apply nature inspired Genetic Algorithm to obtain optimal feature subset and provide enhanced accuracy when combined with existing classifiers. Further it can be used to make clinically relevant implications that will effectively aid in the timely intervention and accurate diagnosis of the disease to potentially enhance the patient care by suitable diet and medicinal recommendations that pave the way for efficient treatment outcomes.