1. A method for performing multi-objective asset optimization and decision-making using predictive modeling, comprising: building at least two predictive models for an asset, comprising: categorizing operational historical data by at least one of: controllable variables; uncontrollable variables; output objectives; and constraints; selecting at least two output objectives or constraints; and identifying at least one controllable or uncontrollable variable suitable for achieving the at least two output objectives or constraints; inputting the at least one controllable or uncontrollable variable to each of the at least two predictive models; validating each predictive model; if results of the validating indicate a confidence level above a specified threshold, applying a live data stream of inputs to the predictive models; if results of the validating indicate a confidence level at or below a specified threshold, selecting at least one alternative controllable or uncontrollable variable for input to the predictive models; performing multi-objective optimization using the predictive models, comprising: specifying search constraints, comprising: upper and lower bounds for each input variable; tolerance levels representing a range of values for achieving optimal output objectives, and constraints; applying a multi-objective optimization algorithm; generating a Pareto Frontier, the Pareto Frontier including optimal input-output vectors; and selecting a Pareto optimal input-output vector.