Since Warren Weaver presented his article 'Science and Complexity' in 1948, the term Complexity has been appearing with increasing frequency in scientific and even not strictly scientific fields.However, the review of many Complexity conceptualization and measurement proposals, shows considerably different approaches, both in the way complexity is measured as in the use of the term 'complexity' itself to designate seemingly different issues.And it is necessary to answer the following question: Is there a perspective that allows us to reconcile and explain this variety of approaches?The hypothesis that we defend in this book is that there is such perspective. We use the term com-plex referring to apparently different 'objects' but with a common quality; the presence of restrictions in their information [organizational or logical rules] produces the emergence of meanings not implicit in their parts; the properties of the object as 'entity' are not the sum or superposition of the individual properties of each of its parts.We prove that object's Complexity must be reviewed from four issues [Organization, Emergence, Meaning and Logic] which present recursiveness and interdependency relationships, though from some perspectives the ideas and Emergence and Organization will be more important, while from other perspectives the ideas of Meaning and Logic will be.This perspective that we have designated as comple[x]us [because it essentially refers to the term's etymology] constitutes a framework that help us understand the use of the term Complexity in contexts -or referring to objects- that may be very different: systems, information sources, tasks and even 'ways of thinking'.To reach it, it will be necessary to review various fields of knowledge including Systems Theory, Communication Theory, Algorithmic Information Theory, different approaches to measure complexity, and some epistemology issues including Complex Thinking and Transdisciplinarity.Based on the above review, we propose an Axioms System, four complexity measures, and some general rules that allow us to undertake the formulation of Complexity from different perspectives and even assess phenomena that have underlying hierarchical structures.And in conclusion, we recap and justify why partial approaches to complexity cannot explain all its current conceptualizations, we review the implications of the proposed perspective and indicate some reasons why understanding Complexity is especially important.It will therefore be a non-linear approach to complexity -as surely should be expected from any approach to the science of nonlinearity- which objective is not only to formalize the issues that allow measuring Complexity, but also to give some 'curves' that provide us with meaningful perspectives or' views' to achieve a global comprehension of Complexity.