In medical diagnostics, variations in hemoglobin levels can reveal a variety of prevalent health conditions. Abnormal hemoglobin is known to be connected with diseases like anemia, diabetes, hematemesis, hematuria, and hemoglobinuria. Consequently, there is a significant demand for advanced detection technologies and precise methodologies to accurately track and assess hemoglobin levels. This study demonstrates the potential of a novel molecularly imprinted nanoparticle‐based sensor system to rapidly analyze hemoglobin levels without the need for a laboratory environment. Hemoglobin imprinted‐poly(acrylamide‐co‐vinyl imidazole) [Hb‐imp‐p(AAm‐co‐VIM)] nanoparticles with high affinity and selectivity for hemoglobin were synthesized and loaded onto the surface of a screen‐printed carbon electrode (SPCE) with a nafion nanofilm. Nafion has selective ion exchange properties and allows for the enhancement of the electrochemical signal. An increase in signal was observed in the presence of 0.5% Nafion. The Hb‐imp‐p(AAm‐co‐VIM)/Nafion‐SPCE system was employed as the sensor surface for the detection of hemoglobin levels in blood. The Hb‐imp‐p(AAm‐co‐VIM)/Nafion‐SPCE system was characterized by cyclic voltammetry (CV) and differential pulse voltammetry (DPV) measurements. The linear working range for hemoglobin was observed to be 0.73–15.54 μM (R2: 0.9934), with a calculated limit of detection (LoD) value of 0.24 μM (3.3 S/N). The sensor system exhibited high efficiency at the biological pH value of 7.4. Furthermore, percent recovery values for hemoglobin in blood samples were observed to be between 90.34% and 103.68%. To determine the selectivity of the Hb‐imp‐p(AAm‐co‐VIM)/Nafion‐SPCE electrode system, the current values of the system were investigated in the presence of ascorbic acid, cysteine, glucose, and IgG. The system exhibited high selectivity. Based on the data obtained, it is evident that the Hb‐imp‐p(AAm‐co‐VIM)/Nafion‐SPCE system can detect hemoglobin in biological environments and has the potential for use in disease monitoring systems.