The aviation industry is increasingly driven to enhance predictive maintenance capabilities. This thesis addresses component-wise condition monitoring of the GEnx-1B engine with fewer gas path sensors using Gas Path Analysis (GPA). Due to a limited number of gas path sensors, the GPA problem is underdetermined, with more health indicators than available measurements. A novel approach is proposed that restructures the underdetermined problem into multiple solvable subproblems and combines their solutions using weight factors, while incorporating companion engine analysis to detect abnormal degradation. The GPA simulations are performed using GSPy, avoiding the computational cost of optimization-based methods. Results show accurate predictions of component health indicators, with strong performance for high-pressure compressor (HPC) and high-pressure turbine (HPT) degradation, while low-pressure components exhibit higher uncertainty. It also captures maintenance events and predicts abnormal degradation prior to failure using companion engine residuals. Overall, the Component Exclusion Method and Companion Engine Analysis enable health estimation of underdetermined gas path cases (like the GEnx-1B), while avoiding high computational costs.