Publisher Summary This chapter examines the mathematical concepts of lean Six Sigma (6σ) engineering strategies. The chapter begins with a description of process modeling, which is the heart of lean six sigma. In mathematical terms, this is expressed as the value of the dependent variable response Y change as a function of independent variables or adjustable variables like x1, x2, x3 . . ., xn of n quantitative factors such that output equals f(input) . Here f is called response function and Y is a dependent variable (in Six Sigma terms strategic objective measurement values or symptom) and x is an independent variable (or cause). The next mathematical concept of lean Six Sigma engineering strategies described in the chapter is that of normal distribution. Following this, the chapter explains many other forms of distributions, such as t-distribution, binomial distribution, Poisson distribution, exponential distribution, and hypergeometric distribution. Subsequently, normal tests (Kurtosis and Anderson) are explained. Finally, the chapter deals with reliability engineering and estimation.