Machine learning, a subset of artificial intelligence (AI), centers on creating algorithms and statistical models. ML tools empower computer systems to acquire knowledge and autonomously make predictions without explicit programming. Data mining involves extracting valuable insights, patterns, correlations, and trends from large datasets stored in data repositories. The main objective is to convert raw data into actionable knowledge. This paper considers sustainable development goals-related datasets for applying ML techniques to find suitable variables for future predictions. The ten familiar machine learning approaches are Gaussian processes, linear regression, random forest, and REP tree. Numerical illustrations are provided to prove the proposed results with test statistics.