The aim of the present assay is to provide a simple algorithm as well as a didactic theoretical framework that may serve as an introduction to understanding modern habitat suitability (HS) modelling techniques in Ecology and Biogeography. The proposal is built on classical descriptive statistics and classical ecological theories. Shelford's theory of a bell-shaped curve of tolerance is used to assign suitability values to individual sites, according to their deviations from the optimal requirements of a hypothetical biological species. Liebig's law of the minimum is applied to assess the overall suitability given a multivariate set of environmental factors. To illustrate the algorithms, hypothetical examples are given with small sets of values simulating data extracted from maps with environmental information. The reader/lecturer is invited to reproduce these small-scale examples using common spreadsheet software or to apply them at a large scale using raster datasets in any advanced geographic information system. As didactical outcomes, this algorithm allows introducing students to the general form and applications of bell-shaped exponential equations (with mu and sigma parameters), understanding the convenience of the law of the minimum when analysing multivariate datasets and the philosophical understanding of certainty/uncertainty when working with the multidimensional niche theory.