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Researchers today have found out the importance of Artificial Intelligence,and Machine Learning in our daily lives, as well as they can be used to improvethe quality of our lives as well as the cities and nations alike. An example ofthis is that it is currently speculated that ML can provide ways to relieveworkers as it can predict effective working schedules and patterns whichincrease the efficiency of the workers. Ultimately this is leading to aWork-Life Balance for the workers. But how is this possible? It is practicallypossible with the Machine Learning algorithms to predict, calculate the factorsaffecting the feelings of the worker's work-life balance. In order to actuallydo this, a sizeable amount of 12,756 people's data has been taken underconsideration. Upon analysing the data and calculating under various factors,we have found out the correlation of various factors and WLB(Work-Life Balancein short). There are some factors that have to be taken into seriousconsideration as they play a major role in WLB. We have trained 80% of our datawith Random Forest Classifier, SVM and Naive Bayes algorithms. Upon testing,the algorithms predict the WLB with 71.5% as the best accuracy.

An Experimental Analysis of Work-Life Balance Among The Employees using Machine Learning Classifiers