Metrization theorems characterize when a topological space's topology comes from a metric: typically requiring second-countability or local finiteness combined with regular and Hausdorff separation. The Urysohn metrization theorem is the key result. These theorems clarify which topological properties are metric in nature.
You have already seen that every metric space carries a natural topology — the collection of all open balls. But the converse is not automatically true: given an abstract topological space defined by specifying which sets are open, can we find a metric that generates exactly those open sets? This is the metrization problem, and it matters because metric spaces have special structure: distances, limits, Cauchy sequences, and completeness. Knowing that a space is metrizable means all these tools are available even if no explicit distance formula was given at the outset.
The prerequisites you've studied put the necessary vocabulary in place. A space is second-countable if it has a countable basis — a countable collection of open sets such that every open set is a union of basis elements. It is regular (T₃) if points can be separated from closed sets by disjoint open sets. The Urysohn Metrization Theorem states: every second-countable, regular Hausdorff space is metrizable. The conditions are close to necessary as well — a metrizable space must certainly be Hausdorff, and must satisfy strong separation properties. Second-countability provides the "size control" needed to construct a metric, while regularity and Hausdorff together provide enough separation to distinguish points cleanly.
The proof strategy is illuminating: you use the Urysohn Lemma (which requires normality, obtainable from regularity plus second-countability) to construct a countable family of continuous real-valued functions that separate points. From this family you define a metric by a weighted sum of squared differences, and you verify it generates the original topology. The metric is not unique — metrization is an existence result, not a uniqueness result — but the key insight is that continuous real-valued functions carry the geometry of the real line into the abstract space, and that's what distance ultimately is.
For spaces that are not second-countable but are still "locally nice," the Nagata–Smirnov Metrization Theorem provides a more general criterion: a space is metrizable if and only if it is regular Hausdorff and has a σ-locally finite basis. This characterizes metrizable spaces completely. The practical lesson is that metrization theorems act as a bridge: they tell you when the intuition and theorems you know from metric topology apply to more abstractly-defined spaces. Whenever you encounter a topological space defined axiomatically and you want to use tools like completeness or uniform convergence, checking the hypotheses of a metrization theorem is your first step.