Chebyshev polynomial has been used for efficient ECG signal reconstruction. There exists a necessity to accurately rebuild these signals based on the predicted Chebyshev coefficients, particularly in cases when the beats have been captured using non-uniformly sampled signals. An algorithm has been devised for ECG signal modeling using the Chebyshev polynomial, comprising multiple sequential steps. The process involves filtering and segmenting of the signal, transposing it into the polynomial's domain of definition to calculate coefficients, and subsequently using these coefficients for ECG signal reconstruction. The algorithm's performance assessment is conducted using the signal acquired by the BIOPAC MP45 device. It's crucial to preprocess noisy signals and consider segment length for accurate polynomial fitting. Polynomial models work best when the signal can be reasonably approximated by a polynomial function. Prior to employing polynomial fitting, it is essential to conduct thorough preprocessing of the ECG signal, encompassing noise reduction, baseline wander elimination, and artifact removal, to ensure its integrity. The signal is filtered through a Butterworth filter to eliminate unwanted frequency components between 0.5 Hz and 100 Hz, a notch filter to counter powerline interference, and a moving average filter to smooth the signal and minimize noise. Accurate ECG beat reconstruction using approximate Chebyshev coefficients has been demonstrated successfully. Notably, the Butterworth LPF achieved an impressive MSE value of 0.0067916. Additionally, the MSE decreased from 0.0062198 for a 5 s segment to 0.0057045 for a 15 s segment when applying the Butterworth BPF.