The transition from mild to severe allergic phenotypes is still poorly understood and there is an urgent need of incorporating new therapies, accompanied by personalized diagnosis approaches. This work presents the development of a novel targeted metabolomic methodology for the analysis of 36 metabolites related to allergic inflammation, including mostly sphingolipids, lysophospholipids, amino acids, and those of energy metabolism previously identified in non-targeted studies. The methodology consisted of two complementary chromatography methods, HILIC and reversed-phase. These were developed using liquid chromatography, coupled to triple quadrupole mass spectrometry (LC-QqQ-MS) in dynamic multiple reaction monitoring (dMRM) acquisition mode and were validated using ICH guidelines. Serum samples from two clinical models of allergic asthma patients were used for method application, which were as follows: (1) corticosteroid-controlled (ICS, n = 6) versus uncontrolled (UC, n = 4) patients, and immunotherapy-controlled (IT, n = 23) versus biologicals-controlled (BIO, n = 12) patients. The results showed significant differences mainly in lysophospholipids using univariate analyses in both models. Multivariate analysis for model 1 was able to distinguish both groups, while for model 2, the results showed the correct classification of all BIO samples within their group. Thus, this methodology can be of great importance for further understanding the role of these metabolites in allergic diseases as potential biomarkers for disease severity and for predicting patient treatment response.