Abstract: This is aimed to implement Random Forest (RF) classification machine learning algorithm performance and investigate its properties. Implementation and all experiments are done in R environment using the Kaggle Dataset-Titanic: machine learning from disaster. Variable importance is estimated for the dataset using this method. Finally, variable selection using importance ranks influence on RF classification rates is analyzed.