This paper introduces a possible way to use a multivariate methodology, called principal component analysis, to reduce the dimensionality of condition state database of bridge elements, collected during visual inspections. Attention is paid to the condition assessment of bridges in Estonian national roads and collected data, which plays an important role in the selection of correct statistical technique and obtaining reliable results. Additionally, detailed overview of typical road bridges and examples of collected information is provided. Statistical analysis is carried out by most natural reinforced concrete bridges in Estonia and comparison is made among different typologies. The introduced multivariate technique algorithms are presented and collated in two different formulations, with contrast on unevenness in variables and taking into account the missing data. Principal components and weighing factors, which are calculated for bridges with different typology, also have differences in results and element groups where variation is retained.